This topic is bringing out the hallucination-panic crowd.
It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.
Use the LLM as search technology: string match -> semantic search -> search intelligence.
This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.
Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.
Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.
A great strength of LLMs is how they provide useful answers even if the prompt has glaring spelling or grammatical mistakes. If your prompt is not great, as you said, they will reply in a way that helps you identify that flaws, and learn how to steer the model better.
They're amazingly useful tools, but they're nowhere the level believers want them to be, not yet.
The readme on Github does say the system produces hallucinated sources https://github.com/anonnerdfrenzy/survival-llm#how-the-model..., but really you're correct, for this kind of highly targeted use case the LLM's summary could probably be ignored entirely and the system could work extremely well even just as a search engine: index all of the content up front, chunked by paragraph and maybe enriched with a HyDE step, have the LLM facilitate running a handful of hybrid keyword/semantic searches based on the user's question and reranking the results, and show the exact pieces of text in the corpus that are most responsive to their question. No summary needed.
Query expansion and reranking are both valuable and things that even small LLMs are pretty good at. People are broadly not great at writing search queries, so a system that takes a poorly phrased question, turns it into several different actual search queries and then merges and sorts the results by relevance can have a big impact. All the better if the AI can ask the user some clarifying questions.
Nevermind hallucinations, the donkey-work is important; why bypass the hours of research, which trains our in-built LLM and can lead to new realizations, and get the carrot without much effort? This LLM stuff feels like a candybar; the anticipation of the magic feels good, the thing tastes good while you're eating it, and everything thereafter is shit, but we easily forget, and reach for the next candybar.
I appreciated Blindboy Boatclub's take in his podcast episode "Artificial intelligence is Disgusting and it will never replace Artists" from 2026 March 17. I also appreciate Electrical Engineer & Computer Scientist Timnit Gebru's perspective on these stochastic parrots.
While intraspecies diversity confers, up to a point, a survival benefit, consider the long-term consequences of playing this particular game.
We don't have to eat every candybar the rich mostly-guys ply us with.
The premise in this case is to get answers quickly in an emergency situation. You don’t want to tell the person with a burn injury to wait a bit since you always wanted to learn how burns are treated.
In a true emergency, there are often many cases where you need not just information retrieval, but "thinking and reasoning" to deal with unprecedented situations, right? Is it technically possible to balance lightweight local performance with thinking capability, while avoiding the risk of hallucinations in life-or-death instructions?
The summarization is the main issue here. A fuzzy search is far less controversial. The LLM companies have done a good job synonymizing "AI" with their products however.
Multiple times yesterday I caught Claude giving slightly incorrect information about things it had read in docs and source code. Its info was accurate enough to be plausible, but it was still wrong. And when I pointed that out, it agreed that it had overstated or made statements without verifying them.
It would be terrible to be doing an emergency medical procedure and have an AI backtrack on something it had told you to do.
The AI should have a tool that it can use to quote an underlying document. The AI itself would not be responsible for filling the quote; that would be done by the interface which deterministically quotes the requested section.
I like using Gemini Notebooks, but this is one of my current frustrations. At least with the current UI, I can see the document getting quoted, but not the actual quote to verify what it's saying or to see the context of the quote. So I'm forced to find the content manually or just trust the LLM got it right.
There really needs to be some kind of "double check" mechanism built into these things instead of putting 100% of that on the consumer. Humans simply don't have the mental capacity to double check the amount of data coming out of LLMs.
The "double check" mechanism for medications is: We tell people not to take medical advice from anyone who is not trained in medicine.
This is not a new problem. The internet has been full of nonsense since the 1990s (at least). Gossip and malicious rumors are as old as language.
It is not realistic to stop the generation of nonsense (of the malicious or the stupid sort). We should train people to detect and ignore nonsense when they hear it.
This advice is inadequate and impractical. Most people don't have access to doctors who spend enough time on them to really get to the bottom of all issues.
In most countries, there are simply too many patients per doctor, meaning it's a conveyor belt of "good enough" 5 minute appointments.
People will turn to other modes of discussing and analyzing their problems if they go to professionals repeatedly and the problem still isn't solved. Just telling them not to do so or to ignore 100% of it isn't going to solve that.
> It is not realistic to stop the generation of nonsense (of the malicious or the stupid sort).
Seems like a big statement. Why is it not realistic? People are already doing it manually by having one LLM fact check output from another.
The difference is back then we had the adage "don't believe everything you read online" that helped adjust our priors. Today, however, these companies are specifically marketing themselves as the source of ground truth. Your boss, or your school that a generation ago banned wikipedia, is now demanding you to use these tools and make the work dependent on them.
It’s fine and safe, it just feels a bit silly. Yes, I could have an LLM read a ton of stuff and generate a list of suggestions on the fly.
Or I could have an honest to god farmer make that list now, ahead of time. Regular search could absolutely surface that.
But also, as someone who does hydroponics, you’re going to end up reading the papers anyways unless you’ve done this a lot. It’s not easy to pick out something like low iron from too little light.
This downloads a library of mostly kiwix wikipedia information and produces a full text SQLite index that is live searched by the model and then the model reads and summarizes the information.
Interesting thing is that when I asked a follow up question it answered but showed: This answer came from what the AI already knows, not the library, so there's no source to check. Ask “look that up” to get one.
When I asked "look that up" it was able to. It highlights relevant sections.
The information it was working off in my case was WikiHow and there aren't any citations in that information.
Running on a 32GB Mac M1 using Qwen 27B. Ollama is showing as taking 19GB steady state and 23GB while answering on Activity Monitor (sometimes a little more and sometimes a little less).
Its amazing this can be done, but it seems like someone should be able to develop a much smaller model that can be used reliably for this use case. There are smaller models available to use and download but it is stated that they have some reliability issues.
Interesting. I have a mac mini I run headless dedicated for LLM inference. Do you know if I could run project nomad on a linux box but use qwen on the mac for the AI stuff? I can't find any info on if this configuration is possible.
I set this up on my machine and tested it with the following question:
How can I build a bow drill so I can start a fire?
It got it partially right: spindle, bow with string tied the correct way, and fire board. But then it flubbed by saying you put the spindle between both hands and move your hands back and forth to rotate the spindle and create the necessary friction… this totally ignores using the bow to rotate the spindle! It also mentioned “fanning the sparks” but there is absolutely no way your bow drill is going to create sparks.
I asked a frontier model to check the survival LLM’s conversation trace and it pointed out the errors.
I didn’t see obvious errors in the other 3 prompts I used, but this one seemed pretty egregious for a survival LLM.
I thank the creator for making this, but take it with a grain of salt.
That's why the question was whether it gave sources, not whether they asked it to go check sources. Yeah, LLMs suck and you should always assume false information. 80% accurate is not production ready.
I'm actually not sure I agree- I think giving a very specific response to your question, even with a 10% chance there is a mistake, along with giving you sources, is pretty helpful: It gives you a good starting hypothesis that you can then validate.
llms tend to make different types of errors than humans, so with this process each can guard against the errors of the other.
Its just more work. If you have to verify from the sources anyhow, why spend effort reading the prompt to begin with? It just wastes your time and maybe even pollutes your subconscious with incorrect information.
Those are more militia LARP relevant than actual survival relevant in fairness but the other gaps are pretty bad. You can definitely have a useful too without that info and for disaster situations most people don't have to go into the level of hunting their own food so I guess it's more of a question of how long and how deep the disaster you're looking at info on is expected to go.
Yeah that's where it comes down to what kind of disaster scenario you're actually thinking about preparing for. Though there's no amount of post disaster perusing of those Army manuals summarized by an LLM that's going to help you actually implement anything in them. The skill to use the info in those books without being a liability to yourself and others requires actual practice.
Also the way groups actually survive scenarios is rarely around actual fighting and is vastly more dependent on actual survival skills, cooperation, and organizing. The lone (or small group) survivalist fantasy is mostly an American larp.
Considering the tendency even now of LLMs to hallucinate, and the hardware requirements for any kind of LLM -why not just gather those resources into some sort of local archive that can be searched without an LLM?
This seems redundant and requiring more overhead while providing less reliability than something like Kiwix to me.
Not sure about how the code in this project works. But the way I see it, an LLM+chat is a great interface for information. If you then connect it to a db with the knowledge/articles you need, then you get a great way to navigate it, without needing the model to memorize all the info
I think that if I were to build this I might skip the LLM and just setup a nice interface to the source files using qmd style search. [0]
That way the tiny model isn't acting as a potentially incorrect interpreter but you still get semantic search to help you find the right documents quickly.
I suppose there is something to be said for a good summarization, I just worry that these tiny models aren't really GOOD summarizers.
Awesome, I didn't know qmd style search, thank you!
I'm all up for using the better/simpler task for the job. That's been a thing lately also with the Jev/decision models hype, most of those things can either already be done by a pretrained classifier[0], or you can start with a bigger model and then train your smaller/adhoc one when you have some data (it doesn't even take much for most applications, you can get about 95% accuracy on email classification with 50-100 examples)
I agree with the OP; this technology does not seem an appropriate fit for survival equipment. By definition survival scenarios can be life and death. Even one "You're absolutely right!" level mistake from an LLM could give a user bad information, leading to John Doe eating a mushroom he really should not have eaten.
I agree with your point, but if John Doe is foraging mushrooms without experience of the local flora (which I doubt this archive contains), then John Doe is kinda asking for it.
The bigger issue in this context would be canning, such as incorrectly explaining the mechanisms to avoid botulism (acid and/or pressure canning), or perhaps incorrectly wiring in repairs. However, again, it’s best to practice with these prior to emergencies anyway.
It should be noted though, that the model does source its claims, so you can fact check it and should review this information regularly.
Slight OT Survival tip, if you are starving don't go for mushrooms in the first place (unless you really, really know) - even if you get the right one, they don't contain much energy for you to burn anyway. The larves you often found in them, probably contain more. So mushrooms are a nice addition (and in rare cases good medicine), but for survival you should focus on something else.
It already is a local archive that can be searched independently, but the LLM does RAG and is, according to them, 95% accurate. It can be useful if you don’t remember where to find a source/what words to search for, but even a durable device with Kiwix would be useless in a a lot of survival situations people imagine.
Undoubtedly useful in the right contexts, particularly for local repair or homesteading, but “survival” does imply that this would be more useful in an SHTF situation.
Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read.
Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.
I like this "both / and" approach. Restructure this project to have the LLM source from local Kiwix data you've selected to make available offline, rather than a source of data you're unfamiliar with. References point directly to your Kiwix library.
I think that for situations like this we should invent a device that can hold information for an arbitrary amount of time even without electricity. Maybe we could call it "BOOK" or something like that.
This isn't clever or insightful. You can of course condense down critical information into a survival handbook, but in existential crises you don't necessarily know in advance what you'll need to know. Wikipedia (as a benchmark repository of knowledge) is ~5 million pages and would require a decent-size room to store if printed out. By contrast, a laptop + solar panel can fit in a backpack. SD cards/USB sticks with the capacity to store all of Wikipedia are a few $ each.
If things are so bad that you need to factor in the non-operability of any electronic devices, how many indestructible paper libraries are you planning to build and manage in advance, and at what budget?
I don't think Wikipedia is a good benchmark here. Try 30 random articles and see how much of that information you would want to have with you in an emergency survival scenario.
Either way the comparisons here are unfair. An LLM that runs off a backpack-sized solar panel and a laptop might be a substitute for a broad, low quality, surface-level encyclopedia but it's many orders of magnitude worse than a library of books.
I would argue that in a survival situation the accuracy of information becomes even more important. If an LLM to misidentifies a plant (or a medical condition, its treatment, etc.) it could put you in an ER, but in a survival situation that could kill you.
Why not both? After the collapse of civilization, as long as you can maintain the computer running, you could educate the next generation as soon as they could write. Maybe they will bypass the local agent as they learn their way into the library, to save energy.
Consider they won't have access to the plentiful practice opportunities we have now, most resources would have to be spent with a practical goal.
A field guide to foraging for edible mushrooms will probably be more practical than naïve use of an LLM: “can I eat this mushroom?” is an exercise in trust that I will maybe never be comfortable with.
But “how do I effectively forage for edible mushrooms” is a great stepping stone.
Survival implies that energy would definitely be a very limited resource. Using it to replace knowledge is just... I can't describe it even. Why not just learn it on our own and keep a small guidebook in your backpack. Our overrelience on computers and now LLMs, even for basic life-saving knowledge is simply our way of going the way of the dodo... I use frontier models at work, I definitely get more done. However I will never use it as a replacement of my own knowledge.
That seems to have been mostly solved through scale. I was asking Opus 5.5 about some obscure stuff and it kept hedging "this is from memory since I don't have internet access" (it's sandboxed), "I'm reasonably sure about this but not about the numbers" etc.
Even though it was obscure enough that Google couldn't easily find the paper that Opus remembered (I couldn't find it at all with the traditional search results; the AI summary found it on my third try), it actually didn't hallucinate it.
In fact I can't remember Opus 5.5 ever hallucinating. They've clearly done some work on that.
Obviously this local LLM is going to hallucinate all over you though.
For one-off questions, a local archive makes sense.
This is more for elaborate projects where you don't know precisely what you are looking for. Questions I can think of in a survival scenario:
- my solar panel connector is broken. We only have 8 hr battery left. Can you tell me how to DIY repair it with the following parts
- we want to receive emergency FM broadcasts from the state. Give me steps on how to receive it on Flipper Zero with this breakout board I found in my spare parts
- with the dewalt drill and these parts, can you tell me how to build an outboard motor for the canoe. We need to get outta here before the flood goes up further
I might not know the trouble-shooting steps for a problem I'm having. LLMs may give poor answers, but they can help me find documents with good answers. That would be enough for most people.
I'm not a doomsday prepper but man if you need to run an LLM locally during the apocalypse to figure out how long your food is going to last, I feel like you are in for a tough time.
This kind of stuff really feels like knowledge that probably shouldn't be offload to AI but rather learned and practiced. Again, I don't have a bunker in my backyard but seems like a weird use case.
I also don't think the showcased response to the food question is any good?
Throwing out food that was at 6 °C for 2 hours without tasting it is really paranoid, the answer should be "it depends". If not following government advice/requirements on safe storage conditions (which is tailored to high risk populations) meant certain illness then I would be seriously ill at least once a week, but I've never been.
I would be waaaay more worried about catching a norovirus from someone who didn't wash their hands than raw meat being kept at 4-8C for 12h.
I actually thought of writing a whole blog post just on this- That is such terrible survival advice, OF COURSE in an emergency you can eat stuff from the refrigerator even after 2 hours.
It is also really dumb to do that if there isn't an emergency
I've never maintained an internal combustion engine but always figured in an apocalypse I'd figure it out with books if needed. I agree that many folk would suffer hard, not knowing how to recognize viable food or even cook it.
I feel like there is a big misunderstanding here. In my house, we've been doing a lot of light "prepping" lately. Not for the apocalypse, but for simple emergency situations for a few days to a week.
The UK government has been pushing hard for the public to stock enough food and water for at least 3 days. We have weeks of supplies.
My huge worry is that the country will run out of LNG due to the ongoing war in Iran, Qatar being offline, and Europe not having enough LNG in storage. Plus, a lot of weird weather due to El Niño.
Is an emergency LLM really going to make a difference? Probably not, but I have one on my desktop computer anyways.
You'd be surprised how many people don't even have drinking water stored to get through a few days. That's 2nd most essential after air to breathe.
Same with food. NONE of this type of preparation is difficult, very space / time consuming, or expensive.
As for the LNG situation: worst case is do without heating. Totally doable in UK climate; extra layers of clothing & blankets / sleeping bags do the job (been there, done that in the NL).
Remember we're talking getting through a crisis, not comfort. Although you can have both with more prep work.
Unless you have a general interest in self sufficiency, spending time practicing this is going to be a waste of time given its risk of actually happening. Thats where the llm come in. The most likely scenario isn't some crazy invasion like in CoD games, but more likely temporary dissarray, and even that is fairly unlikely considering how many things are automated now.
> Mac or PC with 16–31 GB | IBM Granite 4.2 8B | 14 of 22 right | 6 GB
So on a regular consumer machine this is going to be wrong nearly half the time. Great! Let’s hope it’s only on the simple stuff and not the “how do I perform an emergency appendectomy”.
Or just.. download the books, and slap a search engine on top of them. It'll be like 10x smaller than the model. "Survival LLM" is absolutely a non-relevant use case.
When you’re living in an igloo trying to stay warm in the hollowed out belly of a cow having a few books around the place is probably more useful than some files on a laptop that ran out of battery just before it got morbidly damp. Plus you can burn them if you really need to.
On the other hand, the laptop struggling to power a good-enough LLM will probably be a great heat source for you in that igloo... for about 45 minutes.
As I said elsewhere, you can always burn the books! And eating a laptop is considerably crunchier and more fraught than chewing through some good old fashioned leather facings, horse glue and nice heavy 120gsm wove.
Yes I slightly mangled that one. But I’m sure there is a survival technique that involves crawling into the body cavity of a hollowed out cow. You probably wouldn’t want to do that in an igloo though. I’m not even sure you could get a cow into an igloo. If standard issue humans are this flawed it’s hardly surprising that top flight LLMs get things so wrong sometimes.
Recoll it's far smaller and it runs on a potato. It's a desktop search engine which can parse tons of files. Under GNU/Linux just install all the recommended dependencies for APT/RPM. Or just use Flatpak and to hell with transitive dependencies.
We had a set called something like “How to do anything in an emergency” which had instructions for this and more. Alongside lots of creative uses of potassium permanganate.
I’m pretty sure it also told you how to butcher a sheep.
I used to be obsessed with it as a kid. The spectre of nuclear war and a three volume handbook on how to survive the impending apocalypse with nothing more than a plastic bucket, a packet of potassium permanganate, some charcoal and string. The late 80s and early 90s were a wild time to be a kid.
Have you re-read it recently? Some of those books were fun to read but not really something to use as a field manual. Then again some of them were great! I had a book that started with explaining how a battery and a light globe worked, went through how to make a DC motor out of copper wire and a cork, and ended with a crystal radio and I think a radio homing beacon (the latter might have been in another book.)
I have not, sadly. But I’m pretty sure I also had the book you mention. My brother and I made our own motor and many other things that would now be considered entirely unsuitable for 10 year olds to be doing. Copper sulfate crystals seem like a great idea until you have to explain why the playroom carpet has melted.
I have a bunch of military field manuals and survival guides, but they all implicitly presume the existence and contactability of civilization sooner or later. Realistically, some pocket computer(s) and solar charger(s) will store far more information, be far more portable, and give you more carrying capacity for things like medical supplies, rope, tools, and other hard-to-substitute items.
The advantage of a turn-by-turn flow (honestly the chat interface was genius) is that with a little human intervention you can get much better results out of even silly models. The model of choice is strange, though. Not a particularly good one.
Either it depends a lot on the model, or I’m bad at chat, or both, because in my experience once a chat starts going off the rails it’s pretty hard to correct the initial misconception. I find it works better to backtrack to just before the misconception and edit my previous response to head it off at the pass.
Definitely agreed that it's better to not have some text in the context than to have some that needs to be opposed. I suppose I meant steering prompts are a non-obvious innovation to LLM interaction.
People apparently like Granite for RAG specifically. I'm not aware of any evaluations with numbers though, so I'm not sure if it's a real difference or just vibes.
this reminds me of something I built pre-LLMs that i called a "doomsday computer"
it was a raspi with a couple 18650s and bms taken from a drill battery combined with a pico-projector and a laser keyboard stuffed in a waterproof acrylic cube with a stack of sd cards filled with stuff like the survivor library and an offline copy of wikipedia.
complete with fold out solar panels and circuitry taken from one of those amazon solar phone chargers.
worked well for a few hours at a time at night while camping. eventually i was planning to add a retropi sd and a best of music sd (like classical and the rolling stone magazine top 500)
I give it about 50/50 the internet goes down or becomes effectively unusable for weeks, maybe months, at some point in the next 5 years given abysmal commitment to cybersecurity from almost every company that exists.
Some kid with the right prompt will supply chain attack a dependency of a dependency of firmware for border routers just to watch the world burn, or runaway AI swarms will saturate all bandwidth. Or a Linux kernel zero-click vuln. So many ways this can happen.
If every single example posted has hallucinations and the response is "it's your fault for not checking the sources" then it's obvious that an LLM isn't the right tool for the job. A search engine works perfectly fine for these kinds of datasets.
I have some property that doesn't really get cell reception in the summer, and even in the winter the reception is at-best spotty. I use granite and qwen together with a manually curated set of books, articles, etc. to get work done while disconnected. I tend to update the set of resources before leaving town because I'm generally intentionally disconnecting to focus on deep work. Building a workflow that makes that possible has helped me build out a setup that replaces a ton of my day-to-day anthropic/openai use even when I'm near fiber.
It is interesting how, even pre-llms, offline computers change the nature of a lot of activities. E.g., about once a year I'll walk do a random walk in the woods for a few days without paying much attention to maintaining a bearing. With maps and compasses it's a whole skill set to find your way back. With a phone and downloaded maps you just kinda press the power button and check your heading every hour or two.
The "survival" use-case is interesting. I fear a lot of the practical applications of that knowledge are either time-sensitive (e.g., RAG on a "Stop The Bleed" course won't help because by the time you learn the patient is dead) or require tools+skills that aren't easily improvised completely from scratch in high-stress situations (e.g., building shelter or even really simple stuff like building a fire when it's very cold out). And for other stuff common sense prevails (e.g., power out -> keep fridge closed).
I just use llama cpp , it's light weight, I think you create your own integrations, with a larger model so llama cpp can interract with scripts that would browse the web, control your computer etc... propably will have to download some pip packages
I would suggest Hammunition, https://github.com/Renegade-Penguin/Hammunition with install docs at https://renegade-penguin.github.io/Hammunition/ . Hammunition offers much more info than Nomad for SHTF type emergencies. Hammunition uses KIWIX tools instead of an LLM to search the reference sources that you downloaded (eg. Wikipedia, etc.). You can install it on a Linux distro on a 500 GB external SSD drive that you can pick up for $100 at Microcenter. It is geared toward people interested in ham radio, but you can listen only on the ham radio bands without a ham license.
I'm conflicted here -- on the one hand, you make a good point. Things we take for granted normally are luxuries in a survival sitation. On the flip side, running a generator for a bit to get an LLM to generate schedules, guides, step-by-step that can be edited/followed on a much lower-powered device seems reasonable.
I'm using for the emergency hot tub and hairdryer first. The last thing you want in a state-wide blackout is to be walking around super relaxed but with wet hair..
Solar panels? You can go down to Harbor Freight right now and pick up a setup that will run a laptop or tablet for a while, for a couple of hundred dollars. One wouldn't have to spend a ton more to get a setup that can run a decent PC with a GPU for at least a little while.
I mean, you're probably not going to run it all day, especially not in the part of year with fewer daylight hours, but anything's better than nothing. Plus the same solar setup can be used to power other useful things.
It's pretty cool. But if it's such a small model and small corpus, isn't it almost just as good just to have a static wikipedia-style copy of those key sources (WikiMed, MedlinePlus, Ready.gov, CDC etc.)? Maybe if they (and that could be static too), gave you a "what's going on?" question and then told you what you might not know - i.e. "power is out" -> "make sure you open your fridge as little as possible", "if you have backup battery ensure you turn power hungry devices off" etc.?
All this is interesting, but I always had a question: in a state of disaster or some mishap even if you have an light LLM running - most important is a power source/electricity. Without it nothing will work.
There are quite a few options that people lean on.
- Traditional: a generator. Problem is that you need a fuel tank, but if you are aiming to get through a couple of weeks then that's possible.
- Grid attached battery backup: good because in some places (like the UK) electricity at night is much cheaper than electricity during the day... so you can charge the battery and then save money and get payback on your installation. Bonus point is that if there is a grid outage then you have power, for a day or so if you are careful.
- Grid attached with solar/wind: as above, but you can charge independently from the sun/wind... obviously in some places (like the UK) this has limited utility because the sun don't shine (like today), and the wind can be annoying and difficult as a power source (gearboxes, noise, aesthetics). Can cost in though - because of summer power my panels pay back in 11 years. Small wind turbines seem to be getting more practical but I am no expert.
- Non grid battery backup. These also come with solar now, so you can recharge if it's sunny. These are cheap (<~£1000), hold maybe 2Kw and so can power some devices while the grid is off for a little while. Definitely you can run your phones and computers for a few extra cycles, but people are often looking to run freezers or fridges with medicine with these.
Another thing that folks like to have is grid independent heating / cooking via a woodstove. This is frowned on in urban areas and by eco people but I live in the country and have done my reading and while other people will pop up and decry particulates to be honest I'm keeping my burner so my family will be warm and fed for as long as our food lasts or we don't get looted by the neighbours.
212MB for MacOS and 25MB for Windows? Why are MacOS binaries so large? Is it typical for them to be 10x Windows binary size?
That said, I'm really looking forward to small and quick (latency wise) models are a reality. I can easily see a world where every keystroke, terminal command, etc. goes through a "autocorrect" type model. You could even blend natural language plus terminal program segments and the AI just infers what you intend. Either built-in or a second classifier model, determines if the autocorrect change needs human review first.
Back in 2018 I was working on a project for educating schools in certain parts of Africa and Middle East, on AI. The issue was it had to be air-gapped (no internet guarantees) and small/portable. I ended up downloading Wikipedia (not all of it), and then created a lightweight inverted index (for search) and TextRank (for summaries). The whole thing was on a Raspberry Pi, and installed in a small plastic enclosure. We had many of these and could easily ship them. There was an "AI Learning Module" as well we built, that started with Scratch, and then moved into Python. But if I was to do it all over today, I would probably add a tiny LLM and maybe a small ASR and a TTS model too, and you basically have a completely self-contained AI knowledge assistant in a cigarette box. The point being, you basically also have a "survival AI" you can take with you. Of course you still need electricity...
Great idea, I do a lot of work testing small LLM's in this space and agree if you add some guardrails and train a small embedder, you won't need these large models, as your info is static, you can ship it all as one.
A detail from the benchmarks in that page is that Nemotron Lightning has good results for a MoE model close to Qwen 27B which is dense. Very interesting considering that Qwen 35B MoE stopped being in Alibaba's plans, and curious if Nemotron is equally capable in other bemchmarks.
How are we powering this computer? Maybe be need a bootstrap llm that can answer only that question and runs on a solar device? Or some kinda clockwork bad boy, now you're talking :)
I went through a category 5 hurricane that took down everything. Prepared by downloading as much as I could ahead of time but it wasn’t enough. This, or something similar, would have been a blessing.
Love this. And as a trend, I'd love to see more local/small task-specific models/agents. Experts at helping you with that one thing, leaving the everything-and-the-kitchen-sink to the frontier models/agents
At what point would it be better to download a few real sources and do plain text search? Why risk a hallucination for content that would probably be smaller than the size of the model?!
>The app is the same everywhere. When it opens, it checks your computer's memory and downloads the AI model that fits. More memory means a smarter model.
first thing an emergency tool should require, internet access.
at first glance I figured it'd be an ultra small specialty trained survival model that'd be small and runnable anywhere, sorta like an emergency flavored version of those tiny tts models that have been all over recently.
What this needs is a recipe or script that you can point your local agent at and it builds a bespoke implementation that’s, by definition, highly resilient.
Download a good fast local model e.g. Gemma-4-12B (small machine) or Qwen3.6-35B-A3B (larger memory). Or a Nemotron model, if you prefer that.
Then you'll have both your backup/emergency assistant that runs on your own computer and be gaining skills in a common, frequently-updated, well-supported program.
I am not going to accuse anyone of anything, but this looks suspiciously like the project I have been working on. The dates, the time, the folder structure, the concept. It is a bit disheartening, because it missed the whole point, and it butchered the implementation. No LLM makes sense. Having an LLM in the loop is having the worst of both worlds? Example: My initial use case was to provide schools and traders in rural Africa with at least some sort of free LLM-like capability. They have phones that cost $5. Power cuts, drop of the cellular network. Not just 'No-LLM to prove a point'.
It is also only 5% of the wider scope and I was about to release it under OSS 2 days ago, but wanted add some final finess. Now that this is out, I might as well release it so the concept actually ties to its original goal, and release the scientific papers that date back to Feb. Please ping me on github. Same username as here. Always could do with help.
With all due respect: why does this need an LLM, and this much data? Surely a "classic" knowledge base with a more traditional search bar, running on top of the same data this LLM was trained on would be way smaller, and actually as trustworthy as the source material it surfaces for you?
There are a fair number of people who seem to believe that LLMs contain "world knowledge" and are blissfully unaware of how inaccurate an ungrounded chatbot can be. They ask it questions, it gives them confident and plausible (sometimes even correct!) answers, and they leap to the conclusion that these are useful tools for end-of-civilization knowledge bases. I fought this battle countless times on HN and Reddit, generally unsuccessfully.
This project at least attempts to ground its answers with (presumably) human-vetted sources. That will make it much, MUCH more accurate and truthful than a bare model. But there is still a non-zero chance for it to hallucinate answers, especially when posed a question that it doesn't have any source material in its database.
As for why bother hooking up an LLM instead of a simple search engine, search engines don't synthesize data from multiple sources into a coherent answer for you, but LLMs are (mostly) great at that.
That said, while I like this pattern (LLM + knowledge base) for lots of things, this isn't necessarily something I'd trust with my own (or my family's) survival.
Yeah, without the ability to search the web, a very small model is going to be too dumb to be useful, and maybe even dangerous due to hallucinations. But, there is a point where the knowledge of self-hostable models will surprise you. That point is probably not runnable on the average laptop, though. It's maybe in the ~30B range, but more realistically in the 128B MoE range. I guess in their tests Qwen 3.8 27B got as many right as the much larger Nemotron Super, but I'd bet Qwen 3.8 Flash would be better than either, but it needs 128GB of unified RAM or a big GPU and lots of system RAM to run the 4-bit version.
I think if I had to build an emergency LLM today, that had to run on modest hardware, I'd bet on Gemma 4 12B. It's got excellent reasoning and good vision/audio and speaks 140 languages.
But, I don't know about the "classic" knowledge base theory, though. Is there a high quality curated pile of survival information that could be bundled into a web UI and made searchable in a knowledge base? The LLMs aren't focused on that topic, so there's a lot of wasted space, but they know a little about a lot of things, including survival topics. Combined with Wikipedia, and maybe a few other sources, you're probably better off with one than without.
I guess one could use some huge models plus web search to compile/distill a focused survival knowledge base or LLM.
Edit: Project NOMAD seems to mostly be exactly that. It has authoritative sources in a searchable knowledge base and the tiny LLMs are an afterthought, which is probably what they should be. https://www.projectnomad.us/
On the setup process: "You only click for about 5 minutes; the rest is downloading." On the energy consumption: "A small generator or power station runs it easily"
Five minutes of clicking and a (small) power station is a small price to pay when survival could be at stake.
Bold of you to assume there will be running computers past the nuclear apocalypse. It is much, much more likely that a lot of electronics will be permanently fried by the inevitable EMPs. Distributing practical skills in how to survive is much more useful.
Seems like a remarkably stupid idea as opposed to just having an extensive encyclopedia downloaded with a very thin client you can use to read from it.
In an actual survival scenario power isn't guaranteed and errors of any kind can be life or death. So you need to minimize the resources used to get the thing working.
LLMs have become the software equivalent of using a hammer to solve all your problems. Like others have said, there are much better solutions to provide an enhanced search engine for your survival knowledge.
If you happen to have an app and library of all the maps you want then yes, that is better. You could ask the same about Survival LLM: Why not just grep a survival guide?
The thesis is that someday an LLM might perform better than both. But I agree, not yet.
A survival guide won't answer a question, you need to search it for some sort of keywords, you might not be using the same term or not know what a particular thing is called, and might end up having to read all of it to find the info you need, or not find it at all.
Navigation is a closed task, A* will always find an optimal route as long as your street info is current, you can't do better than that.
It's disappointing that Gemma E4B seems to perform poorly on this (42% accuracy according to the GitHub). It would be nice if a $25 phone could be loaded up with this and stuffed in a EMP proof metal box with a small solar charger. Maybe a finetune or Gemma 5 will get us there.
I can almost guarantee you that by the time you need a survival assistant, you won't be willing to spend gasoline on generating electricity for your GPUs.
(It's helpful for shorter outages. But "survival assistant", I think not, unless you run a compound)
This will come in handy after AI takes over the world.
But kidding aside, this is an interesting reveal on the ease with which a custom LLM can be spun up to fit a particular niche application, especially for systems not meant to host an LLM.
If you're actually offline and need information in a 'survival' situation, I'm not so sure the hallucinatory nature of an LLM is the based way to distribute a repository of information. Additionally, there's no need to fit an LLM entirely in memory.
In a theoretical scenario where the internet is gone and isn't coming back: If you can deal with a very low token/second rate there's no reason not to store 'offline' a much larger model like qwen 3.8-flash-next or deepseek v4 flash 1017 and use an inference engine which can stream-read it off disk to extract the information you want, albeit slowly. Of course also download and use things that'll fit in RAM, sure, like the qwen 3.8 27B in the linked page. But no need to restrict yourself to only smaller models.
Agreed. Especially for something like this, in which many imaginable situations would require the ability to run on Linux rather than MacOS or Windows, pretty strange.
This is just crap. Why would you want something that can give you wrong answers (like 4 out of 20 like in the tables, that is much!) - in an emergency?
Please, please do not trust a chatbot in emergencies. There’s a reason why actual survival and emergency preparedness guides include manuals rather than recommend you just use a chatbot: practicality.
Just look at those specs needed for accurate-ish results. You really think your 128GB Mac Studio or Framework desktop is going to be able to work in a real emergency situation? Even if it is, how long will it last? What about those precious seconds waiting for inference?
The danger here is less hallucinations and more, well, everything else about it. Instead of setting this up, take the time to make sure you have a restocked first aid kit and enough water for a week of use by your household. Stock up on meds and non-perishable food. Plan exit strategies and contingencies. Acquire and store little first aid booklets or manuals of common survival tasks in physical form (or hell, throw onto an eReader - infinitely more battery life than an LLM host in an emergency).
This is one of those “sounds good in my head” projects that folks with emergency experience would bristle at. This is a hindrance, not a helper.
No thanks, I'll use a generic model along with trusted sources.
Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
The $100 merely serves as a gatekeeper to prevent people and non-devs to create unlimited developer accounts. It used to be $500 a decade or two ago, and it was worth it even back then, until Apple realized they should probably just give it away almost for free.
> Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
This is a great example of how Apple's "scare warnings" completely work to mislead folks about what they are actually warning you about.
This topic is bringing out the hallucination-panic crowd.
It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.
Use the LLM as search technology: string match -> semantic search -> search intelligence.
This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.
Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.
Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.
A great strength of LLMs is how they provide useful answers even if the prompt has glaring spelling or grammatical mistakes. If your prompt is not great, as you said, they will reply in a way that helps you identify that flaws, and learn how to steer the model better.
They're amazingly useful tools, but they're nowhere the level believers want them to be, not yet.
Yes this has been very useful for me this week. I trapped my middle finger on my right hand in a door and it really messed up my typing.
I tried using dictation but I really disliked speaking to it.
You can write a really messed up sentence and it almost always worked out what I meant.
Quite amazing actually
The readme on Github does say the system produces hallucinated sources https://github.com/anonnerdfrenzy/survival-llm#how-the-model..., but really you're correct, for this kind of highly targeted use case the LLM's summary could probably be ignored entirely and the system could work extremely well even just as a search engine: index all of the content up front, chunked by paragraph and maybe enriched with a HyDE step, have the LLM facilitate running a handful of hybrid keyword/semantic searches based on the user's question and reranking the results, and show the exact pieces of text in the corpus that are most responsive to their question. No summary needed.
Not sure what the LLM is adding there then other than injecting a step into your search that could hallucinate.
Query expansion and reranking are both valuable and things that even small LLMs are pretty good at. People are broadly not great at writing search queries, so a system that takes a poorly phrased question, turns it into several different actual search queries and then merges and sorts the results by relevance can have a big impact. All the better if the AI can ask the user some clarifying questions.
The issue is the opposite of hallucinations where the LLM ignores relevant information.
Sure you can combine this with a regular search but there’s opportunity cost whenever you say LLM + something else rather than just the other thing.
Can a bad LM implementation surface bad references? Yes. Are LMs overwhelmingly useful for research? Yes.
Is a bad LM implementation still useful for research? Shmaybe.
But at this point why even bring a full model into scope in the first place.. just run some cheap embedding retriever
Nevermind hallucinations, the donkey-work is important; why bypass the hours of research, which trains our in-built LLM and can lead to new realizations, and get the carrot without much effort? This LLM stuff feels like a candybar; the anticipation of the magic feels good, the thing tastes good while you're eating it, and everything thereafter is shit, but we easily forget, and reach for the next candybar. I appreciated Blindboy Boatclub's take in his podcast episode "Artificial intelligence is Disgusting and it will never replace Artists" from 2026 March 17. I also appreciate Electrical Engineer & Computer Scientist Timnit Gebru's perspective on these stochastic parrots. While intraspecies diversity confers, up to a point, a survival benefit, consider the long-term consequences of playing this particular game. We don't have to eat every candybar the rich mostly-guys ply us with.
The premise in this case is to get answers quickly in an emergency situation. You don’t want to tell the person with a burn injury to wait a bit since you always wanted to learn how burns are treated.
You also don’t want to get advice like that cooking advice to make a glue pizza.
That's is what medical encyclopedias were built for. Fully offline.
In a true emergency, there are often many cases where you need not just information retrieval, but "thinking and reasoning" to deal with unprecedented situations, right? Is it technically possible to balance lightweight local performance with thinking capability, while avoiding the risk of hallucinations in life-or-death instructions?
The summarization is the main issue here. A fuzzy search is far less controversial. The LLM companies have done a good job synonymizing "AI" with their products however.
Multiple times yesterday I caught Claude giving slightly incorrect information about things it had read in docs and source code. Its info was accurate enough to be plausible, but it was still wrong. And when I pointed that out, it agreed that it had overstated or made statements without verifying them.
It would be terrible to be doing an emergency medical procedure and have an AI backtrack on something it had told you to do.
The AI should have a tool that it can use to quote an underlying document. The AI itself would not be responsible for filling the quote; that would be done by the interface which deterministically quotes the requested section.
I like using Gemini Notebooks, but this is one of my current frustrations. At least with the current UI, I can see the document getting quoted, but not the actual quote to verify what it's saying or to see the context of the quote. So I'm forced to find the content manually or just trust the LLM got it right.
There's this article on a woman dying after ChatGPT "helped" her taper off medication https://www.nytimes.com/2026/10/27/well/ai-chatgpt-medicatio...
There really needs to be some kind of "double check" mechanism built into these things instead of putting 100% of that on the consumer. Humans simply don't have the mental capacity to double check the amount of data coming out of LLMs.
The "double check" mechanism for medications is: We tell people not to take medical advice from anyone who is not trained in medicine.
This is not a new problem. The internet has been full of nonsense since the 1990s (at least). Gossip and malicious rumors are as old as language.
It is not realistic to stop the generation of nonsense (of the malicious or the stupid sort). We should train people to detect and ignore nonsense when they hear it.
This advice is inadequate and impractical. Most people don't have access to doctors who spend enough time on them to really get to the bottom of all issues.
In most countries, there are simply too many patients per doctor, meaning it's a conveyor belt of "good enough" 5 minute appointments.
People will turn to other modes of discussing and analyzing their problems if they go to professionals repeatedly and the problem still isn't solved. Just telling them not to do so or to ignore 100% of it isn't going to solve that.
> It is not realistic to stop the generation of nonsense (of the malicious or the stupid sort).
Seems like a big statement. Why is it not realistic? People are already doing it manually by having one LLM fact check output from another.
The difference is back then we had the adage "don't believe everything you read online" that helped adjust our priors. Today, however, these companies are specifically marketing themselves as the source of ground truth. Your boss, or your school that a generation ago banned wikipedia, is now demanding you to use these tools and make the work dependent on them.
It’s fine and safe, it just feels a bit silly. Yes, I could have an LLM read a ton of stuff and generate a list of suggestions on the fly.
Or I could have an honest to god farmer make that list now, ahead of time. Regular search could absolutely surface that.
But also, as someone who does hydroponics, you’re going to end up reading the papers anyways unless you’ve done this a lot. It’s not easy to pick out something like low iron from too little light.
This downloads a library of mostly kiwix wikipedia information and produces a full text SQLite index that is live searched by the model and then the model reads and summarizes the information.
Interesting thing is that when I asked a follow up question it answered but showed: This answer came from what the AI already knows, not the library, so there's no source to check. Ask “look that up” to get one.
When I asked "look that up" it was able to. It highlights relevant sections.
The information it was working off in my case was WikiHow and there aren't any citations in that information.
Running on a 32GB Mac M1 using Qwen 27B. Ollama is showing as taking 19GB steady state and 23GB while answering on Activity Monitor (sometimes a little more and sometimes a little less).
Its amazing this can be done, but it seems like someone should be able to develop a much smaller model that can be used reliably for this use case. There are smaller models available to use and download but it is stated that they have some reliability issues.
Shoutout to project nomad.
https://www.projectnomad.us/
its got a ton of useful options, preconfigured, integrates pretty easily, and can use any local LLM or data.
Interesting. I have a mac mini I run headless dedicated for LLM inference. Do you know if I could run project nomad on a linux box but use qwen on the mac for the AI stuff? I can't find any info on if this configuration is possible.
Sure can. I did similar.
This looks cool! My thought in OPs post was "Why now use Kiwix?" and Nomad seems to do! Also BYOM is better imho.
I set this up on my machine and tested it with the following question:
How can I build a bow drill so I can start a fire?
It got it partially right: spindle, bow with string tied the correct way, and fire board. But then it flubbed by saying you put the spindle between both hands and move your hands back and forth to rotate the spindle and create the necessary friction… this totally ignores using the bow to rotate the spindle! It also mentioned “fanning the sparks” but there is absolutely no way your bow drill is going to create sparks.
I asked a frontier model to check the survival LLM’s conversation trace and it pointed out the errors.
I didn’t see obvious errors in the other 3 prompts I used, but this one seemed pretty egregious for a survival LLM.
I thank the creator for making this, but take it with a grain of salt.
Did it give you the source(s) so you could double check?
Giving incorrect instructions and saying "go check the sources" is worse than just returning the sources. Aka a search engine.
That's why the question was whether it gave sources, not whether they asked it to go check sources. Yeah, LLMs suck and you should always assume false information. 80% accurate is not production ready.
I'm actually not sure I agree- I think giving a very specific response to your question, even with a 10% chance there is a mistake, along with giving you sources, is pretty helpful: It gives you a good starting hypothesis that you can then validate.
llms tend to make different types of errors than humans, so with this process each can guard against the errors of the other.
Its just more work. If you have to verify from the sources anyhow, why spend effort reading the prompt to begin with? It just wastes your time and maybe even pollutes your subconscious with incorrect information.
From what I can tell: - zero firearms or bowhunting content
- no books on hunting or fishing
- no instructions on field dressing animals
- no FM 7-8 or ATP 3-21.8
- no info on reloading ammunition or flint knapping
This feels more like a tool for city dwellers than a serious survival tool.
> - no FM 7-8 or ATP 3-21.8
Those are more militia LARP relevant than actual survival relevant in fairness but the other gaps are pretty bad. You can definitely have a useful too without that info and for disaster situations most people don't have to go into the level of hunting their own food so I guess it's more of a question of how long and how deep the disaster you're looking at info on is expected to go.
I mean, if you are in a scenario where its everyone for themselves, weapon knowledge is going to be absolutely essential.
Yeah that's where it comes down to what kind of disaster scenario you're actually thinking about preparing for. Though there's no amount of post disaster perusing of those Army manuals summarized by an LLM that's going to help you actually implement anything in them. The skill to use the info in those books without being a liability to yourself and others requires actual practice.
Also the way groups actually survive scenarios is rarely around actual fighting and is vastly more dependent on actual survival skills, cooperation, and organizing. The lone (or small group) survivalist fantasy is mostly an American larp.
Considering the tendency even now of LLMs to hallucinate, and the hardware requirements for any kind of LLM -why not just gather those resources into some sort of local archive that can be searched without an LLM?
This seems redundant and requiring more overhead while providing less reliability than something like Kiwix to me.
Not sure about how the code in this project works. But the way I see it, an LLM+chat is a great interface for information. If you then connect it to a db with the knowledge/articles you need, then you get a great way to navigate it, without needing the model to memorize all the info
I think that if I were to build this I might skip the LLM and just setup a nice interface to the source files using qmd style search. [0]
That way the tiny model isn't acting as a potentially incorrect interpreter but you still get semantic search to help you find the right documents quickly.
I suppose there is something to be said for a good summarization, I just worry that these tiny models aren't really GOOD summarizers.
[0] https://github.com/tobi/qmd
Awesome, I didn't know qmd style search, thank you!
I'm all up for using the better/simpler task for the job. That's been a thing lately also with the Jev/decision models hype, most of those things can either already be done by a pretrained classifier[0], or you can start with a bigger model and then train your smaller/adhoc one when you have some data (it doesn't even take much for most applications, you can get about 95% accuracy on email classification with 50-100 examples)
0: http://jeffyclassify.com/blog/when-llms-fail-at-classificati...
I agree with the OP; this technology does not seem an appropriate fit for survival equipment. By definition survival scenarios can be life and death. Even one "You're absolutely right!" level mistake from an LLM could give a user bad information, leading to John Doe eating a mushroom he really should not have eaten.
I agree with your point, but if John Doe is foraging mushrooms without experience of the local flora (which I doubt this archive contains), then John Doe is kinda asking for it.
The bigger issue in this context would be canning, such as incorrectly explaining the mechanisms to avoid botulism (acid and/or pressure canning), or perhaps incorrectly wiring in repairs. However, again, it’s best to practice with these prior to emergencies anyway.
It should be noted though, that the model does source its claims, so you can fact check it and should review this information regularly.
Slight OT Survival tip, if you are starving don't go for mushrooms in the first place (unless you really, really know) - even if you get the right one, they don't contain much energy for you to burn anyway. The larves you often found in them, probably contain more. So mushrooms are a nice addition (and in rare cases good medicine), but for survival you should focus on something else.
It already is a local archive that can be searched independently, but the LLM does RAG and is, according to them, 95% accurate. It can be useful if you don’t remember where to find a source/what words to search for, but even a durable device with Kiwix would be useless in a a lot of survival situations people imagine.
Undoubtedly useful in the right contexts, particularly for local repair or homesteading, but “survival” does imply that this would be more useful in an SHTF situation.
Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare
Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read.
Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.
I like this "both / and" approach. Restructure this project to have the LLM source from local Kiwix data you've selected to make available offline, rather than a source of data you're unfamiliar with. References point directly to your Kiwix library.
>can run on anything now: (link to turbo fieldfare)
Except the build process there requires a specific recent version of swift. Hardly a good definition of "anything"
I think that for situations like this we should invent a device that can hold information for an arbitrary amount of time even without electricity. Maybe we could call it "BOOK" or something like that.
and then we have a lot of “books” so we collect them in “shelves” then in “libraries” then we want to search them etc etc
This isn't clever or insightful. You can of course condense down critical information into a survival handbook, but in existential crises you don't necessarily know in advance what you'll need to know. Wikipedia (as a benchmark repository of knowledge) is ~5 million pages and would require a decent-size room to store if printed out. By contrast, a laptop + solar panel can fit in a backpack. SD cards/USB sticks with the capacity to store all of Wikipedia are a few $ each.
If things are so bad that you need to factor in the non-operability of any electronic devices, how many indestructible paper libraries are you planning to build and manage in advance, and at what budget?
The pedanticty (or is it pedanticness???) on hn is astonishing sometimes.
If there's any place to get an answer it's here.
Bravo my friend. And I mean that in a good way. Love me some diversity.
I don't think Wikipedia is a good benchmark here. Try 30 random articles and see how much of that information you would want to have with you in an emergency survival scenario.
Either way the comparisons here are unfair. An LLM that runs off a backpack-sized solar panel and a laptop might be a substitute for a broad, low quality, surface-level encyclopedia but it's many orders of magnitude worse than a library of books.
I would argue that in a survival situation the accuracy of information becomes even more important. If an LLM to misidentifies a plant (or a medical condition, its treatment, etc.) it could put you in an ER, but in a survival situation that could kill you.
> and the hardware requirements for any kind of LLM
You can run bonsai2 27b on basically any gaming GPU from the last 15 years including on game consoles.
Everyone has access to this stuff now if they bothered to look beyond the marketing from big labs trying to collect subscription revenue.
I work on compilers, kernels, and operating systems using exclusively consumer GPUs.
Why not both? After the collapse of civilization, as long as you can maintain the computer running, you could educate the next generation as soon as they could write. Maybe they will bypass the local agent as they learn their way into the library, to save energy.
Consider they won't have access to the plentiful practice opportunities we have now, most resources would have to be spent with a practical goal.
Nvidia GPUs in the post-apocalyptic radioactive barrens are going to be stupid pricey.
Both. Both is good.
A field guide to foraging for edible mushrooms will probably be more practical than naïve use of an LLM: “can I eat this mushroom?” is an exercise in trust that I will maybe never be comfortable with.
But “how do I effectively forage for edible mushrooms” is a great stepping stone.
> After the collapse of civilization, as long as you can maintain the computer running ...
One of these situations prohibits the other.
Survival implies that energy would definitely be a very limited resource. Using it to replace knowledge is just... I can't describe it even. Why not just learn it on our own and keep a small guidebook in your backpack. Our overrelience on computers and now LLMs, even for basic life-saving knowledge is simply our way of going the way of the dodo... I use frontier models at work, I definitely get more done. However I will never use it as a replacement of my own knowledge.
lots of us have solar cells these days, so energy isn't going to be such a limiting factor
A book is a lot more of a sure bet than you maintaining a computer. We have ancient books today that have survived several civilization collapses.
> the tendency even now of LLMs to hallucinate
That seems to have been mostly solved through scale. I was asking Opus 5.5 about some obscure stuff and it kept hedging "this is from memory since I don't have internet access" (it's sandboxed), "I'm reasonably sure about this but not about the numbers" etc.
Even though it was obscure enough that Google couldn't easily find the paper that Opus remembered (I couldn't find it at all with the traditional search results; the AI summary found it on my third try), it actually didn't hallucinate it.
In fact I can't remember Opus 5.5 ever hallucinating. They've clearly done some work on that.
Obviously this local LLM is going to hallucinate all over you though.
It does, you can ripgrep all through that archive.
For one-off questions, a local archive makes sense.
This is more for elaborate projects where you don't know precisely what you are looking for. Questions I can think of in a survival scenario:
- my solar panel connector is broken. We only have 8 hr battery left. Can you tell me how to DIY repair it with the following parts
- we want to receive emergency FM broadcasts from the state. Give me steps on how to receive it on Flipper Zero with this breakout board I found in my spare parts
- with the dewalt drill and these parts, can you tell me how to build an outboard motor for the canoe. We need to get outta here before the flood goes up further
But this one generates more clicks because "AI" is hot right now and has religious following.
I might not know the trouble-shooting steps for a problem I'm having. LLMs may give poor answers, but they can help me find documents with good answers. That would be enough for most people.
I'm not a doomsday prepper but man if you need to run an LLM locally during the apocalypse to figure out how long your food is going to last, I feel like you are in for a tough time.
This kind of stuff really feels like knowledge that probably shouldn't be offload to AI but rather learned and practiced. Again, I don't have a bunker in my backyard but seems like a weird use case.
Yeah that was my first reaction. In survival mode you want low tech not high tech.
Books are pretty damn good and don't need 500W of GPU
I also don't think the showcased response to the food question is any good?
Throwing out food that was at 6 °C for 2 hours without tasting it is really paranoid, the answer should be "it depends". If not following government advice/requirements on safe storage conditions (which is tailored to high risk populations) meant certain illness then I would be seriously ill at least once a week, but I've never been.
I would be waaaay more worried about catching a norovirus from someone who didn't wash their hands than raw meat being kept at 4-8C for 12h.
I actually thought of writing a whole blog post just on this- That is such terrible survival advice, OF COURSE in an emergency you can eat stuff from the refrigerator even after 2 hours.
It is also really dumb to do that if there isn't an emergency
No, those people are going to die.
This is more of a "preserve the knowledge of mankind for the survivors" type of archive.
I've never maintained an internal combustion engine but always figured in an apocalypse I'd figure it out with books if needed. I agree that many folk would suffer hard, not knowing how to recognize viable food or even cook it.
I feel like there is a big misunderstanding here. In my house, we've been doing a lot of light "prepping" lately. Not for the apocalypse, but for simple emergency situations for a few days to a week.
The UK government has been pushing hard for the public to stock enough food and water for at least 3 days. We have weeks of supplies.
My huge worry is that the country will run out of LNG due to the ongoing war in Iran, Qatar being offline, and Europe not having enough LNG in storage. Plus, a lot of weird weather due to El Niño.
Is an emergency LLM really going to make a difference? Probably not, but I have one on my desktop computer anyways.
You'd be surprised how many people don't even have drinking water stored to get through a few days. That's 2nd most essential after air to breathe.
Same with food. NONE of this type of preparation is difficult, very space / time consuming, or expensive.
As for the LNG situation: worst case is do without heating. Totally doable in UK climate; extra layers of clothing & blankets / sleeping bags do the job (been there, done that in the NL).
Remember we're talking getting through a crisis, not comfort. Although you can have both with more prep work.
I mean its obviously just a fun gag tool the OP made to throw the tool stack on their resume. This post can land them a six figure job.
Unless you have a general interest in self sufficiency, spending time practicing this is going to be a waste of time given its risk of actually happening. Thats where the llm come in. The most likely scenario isn't some crazy invasion like in CoD games, but more likely temporary dissarray, and even that is fairly unlikely considering how many things are automated now.
> Mac or PC with 16–31 GB | IBM Granite 4.2 8B | 14 of 22 right | 6 GB
So on a regular consumer machine this is going to be wrong nearly half the time. Great! Let’s hope it’s only on the simple stuff and not the “how do I perform an emergency appendectomy”.
Honestly, just buy some books.
Or just.. download the books, and slap a search engine on top of them. It'll be like 10x smaller than the model. "Survival LLM" is absolutely a non-relevant use case.
When you’re living in an igloo trying to stay warm in the hollowed out belly of a cow having a few books around the place is probably more useful than some files on a laptop that ran out of battery just before it got morbidly damp. Plus you can burn them if you really need to.
On the other hand, the laptop struggling to power a good-enough LLM will probably be a great heat source for you in that igloo... for about 45 minutes.
As I said elsewhere, you can always burn the books! And eating a laptop is considerably crunchier and more fraught than chewing through some good old fashioned leather facings, horse glue and nice heavy 120gsm wove.
On the other hand, if you know enough to build an igloo, you're probably going to be ok regardless.
"cow in an igloo" sounds like something an LLM would hallucinate.
Yes I slightly mangled that one. But I’m sure there is a survival technique that involves crawling into the body cavity of a hollowed out cow. You probably wouldn’t want to do that in an igloo though. I’m not even sure you could get a cow into an igloo. If standard issue humans are this flawed it’s hardly surprising that top flight LLMs get things so wrong sometimes.
I'd have gone with Bantha in an ice cave myself.
And/or install Kiwix and grab an offline copy of Wikipedia.
Wikipedia rarely (never?) gives enough information to actually build or accomplish anything - it just has a nice clean summary of lots of things.
If you have AI model there it can make any search engine for you as per your needs.
Recoll it's far smaller and it runs on a potato. It's a desktop search engine which can parse tons of files. Under GNU/Linux just install all the recommended dependencies for APT/RPM. Or just use Flatpak and to hell with transitive dependencies.
What is your favorite book on emergency appendectomies?
We had a set called something like “How to do anything in an emergency” which had instructions for this and more. Alongside lots of creative uses of potassium permanganate.
I’m pretty sure it also told you how to butcher a sheep.
I used to be obsessed with it as a kid. The spectre of nuclear war and a three volume handbook on how to survive the impending apocalypse with nothing more than a plastic bucket, a packet of potassium permanganate, some charcoal and string. The late 80s and early 90s were a wild time to be a kid.
Have you re-read it recently? Some of those books were fun to read but not really something to use as a field manual. Then again some of them were great! I had a book that started with explaining how a battery and a light globe worked, went through how to make a DC motor out of copper wire and a cork, and ended with a crystal radio and I think a radio homing beacon (the latter might have been in another book.)
I have not, sadly. But I’m pretty sure I also had the book you mention. My brother and I made our own motor and many other things that would now be considered entirely unsuitable for 10 year olds to be doing. Copper sulfate crystals seem like a great idea until you have to explain why the playroom carpet has melted.
I have a bunch of military field manuals and survival guides, but they all implicitly presume the existence and contactability of civilization sooner or later. Realistically, some pocket computer(s) and solar charger(s) will store far more information, be far more portable, and give you more carrying capacity for things like medical supplies, rope, tools, and other hard-to-substitute items.
Granite is not great at any size. Wonder why they picked that.
Given the whole thing reeks of vibe I don’t think anyone picked anything.
The advantage of a turn-by-turn flow (honestly the chat interface was genius) is that with a little human intervention you can get much better results out of even silly models. The model of choice is strange, though. Not a particularly good one.
Either it depends a lot on the model, or I’m bad at chat, or both, because in my experience once a chat starts going off the rails it’s pretty hard to correct the initial misconception. I find it works better to backtrack to just before the misconception and edit my previous response to head it off at the pass.
Definitely agreed that it's better to not have some text in the context than to have some that needs to be opposed. I suppose I meant steering prompts are a non-obvious innovation to LLM interaction.
People apparently like Granite for RAG specifically. I'm not aware of any evaluations with numbers though, so I'm not sure if it's a real difference or just vibes.
this reminds me of something I built pre-LLMs that i called a "doomsday computer"
it was a raspi with a couple 18650s and bms taken from a drill battery combined with a pico-projector and a laser keyboard stuffed in a waterproof acrylic cube with a stack of sd cards filled with stuff like the survivor library and an offline copy of wikipedia.
complete with fold out solar panels and circuitry taken from one of those amazon solar phone chargers.
worked well for a few hours at a time at night while camping. eventually i was planning to add a retropi sd and a best of music sd (like classical and the rolling stone magazine top 500)
you should document this and make an instructable for it! <3
I give it about 50/50 the internet goes down or becomes effectively unusable for weeks, maybe months, at some point in the next 5 years given abysmal commitment to cybersecurity from almost every company that exists.
Some kid with the right prompt will supply chain attack a dependency of a dependency of firmware for border routers just to watch the world burn, or runaway AI swarms will saturate all bandwidth. Or a Linux kernel zero-click vuln. So many ways this can happen.
Better to prepare a bit and never need it.
Why should I download an 80 GB model that I need proper hardware for, when a couple MB of PDFs is all that's needed?
Reminds me of the time when Docker was thrown at everything.
If every single example posted has hallucinations and the response is "it's your fault for not checking the sources" then it's obvious that an LLM isn't the right tool for the job. A search engine works perfectly fine for these kinds of datasets.
Cool project.
I have some property that doesn't really get cell reception in the summer, and even in the winter the reception is at-best spotty. I use granite and qwen together with a manually curated set of books, articles, etc. to get work done while disconnected. I tend to update the set of resources before leaving town because I'm generally intentionally disconnecting to focus on deep work. Building a workflow that makes that possible has helped me build out a setup that replaces a ton of my day-to-day anthropic/openai use even when I'm near fiber.
It is interesting how, even pre-llms, offline computers change the nature of a lot of activities. E.g., about once a year I'll walk do a random walk in the woods for a few days without paying much attention to maintaining a bearing. With maps and compasses it's a whole skill set to find your way back. With a phone and downloaded maps you just kinda press the power button and check your heading every hour or two.
The "survival" use-case is interesting. I fear a lot of the practical applications of that knowledge are either time-sensitive (e.g., RAG on a "Stop The Bleed" course won't help because by the time you learn the patient is dead) or require tools+skills that aren't easily improvised completely from scratch in high-stress situations (e.g., building shelter or even really simple stuff like building a fire when it's very cold out). And for other stuff common sense prevails (e.g., power out -> keep fridge closed).
The required specs seemed a bit high to me, and I was just looking for alternatives.
I found Project Nomad (https://projectnomad.us) which looks more polished. Any other suggestions?
I just use llama cpp , it's light weight, I think you create your own integrations, with a larger model so llama cpp can interract with scripts that would browse the web, control your computer etc... propably will have to download some pip packages
I would suggest Hammunition, https://github.com/Renegade-Penguin/Hammunition with install docs at https://renegade-penguin.github.io/Hammunition/ . Hammunition offers much more info than Nomad for SHTF type emergencies. Hammunition uses KIWIX tools instead of an LLM to search the reference sources that you downloaded (eg. Wikipedia, etc.). You can install it on a Linux distro on a 500 GB external SSD drive that you can pick up for $100 at Microcenter. It is geared toward people interested in ham radio, but you can listen only on the ham radio bands without a ham license.
Emergencies = No Internet
What about no power? You gonna run your generator for your local model? What are we doing here? Have we lost our way completely?
I'm conflicted here -- on the one hand, you make a good point. Things we take for granted normally are luxuries in a survival sitation. On the flip side, running a generator for a bit to get an LLM to generate schedules, guides, step-by-step that can be edited/followed on a much lower-powered device seems reasonable.
I'm using for the emergency hot tub and hairdryer first. The last thing you want in a state-wide blackout is to be walking around super relaxed but with wet hair..
Generators require the infrastructure that supplies fuel, and you need to have a generator you might not need.
Solar panels and batteries are great for emergencies, and they're useful besides.
> What about no power?
Solar panels? You can go down to Harbor Freight right now and pick up a setup that will run a laptop or tablet for a while, for a couple of hundred dollars. One wouldn't have to spend a ton more to get a setup that can run a decent PC with a GPU for at least a little while.
I mean, you're probably not going to run it all day, especially not in the part of year with fewer daylight hours, but anything's better than nothing. Plus the same solar setup can be used to power other useful things.
Yeah, we forgot information on paper it seems. Flawed as it is I like the idea though..
Smallest model download is 6 GB. I'd rather store a collection of relevant ebooks.
Even in their table it shows the LLM never getting all the questions right.
This is much better waste of space than Apple AI. It was something I was imagining to build, got pleasantly surprised to see it having been done.
It's pretty cool. But if it's such a small model and small corpus, isn't it almost just as good just to have a static wikipedia-style copy of those key sources (WikiMed, MedlinePlus, Ready.gov, CDC etc.)? Maybe if they (and that could be static too), gave you a "what's going on?" question and then told you what you might not know - i.e. "power is out" -> "make sure you open your fridge as little as possible", "if you have backup battery ensure you turn power hungry devices off" etc.?
Living in Miami, this is the kind of thing I'd actually keep on a laptop for hurricane season, when power and cell service can be out for days.
All this is interesting, but I always had a question: in a state of disaster or some mishap even if you have an light LLM running - most important is a power source/electricity. Without it nothing will work.
There are quite a few options that people lean on.
- Traditional: a generator. Problem is that you need a fuel tank, but if you are aiming to get through a couple of weeks then that's possible.
- Grid attached battery backup: good because in some places (like the UK) electricity at night is much cheaper than electricity during the day... so you can charge the battery and then save money and get payback on your installation. Bonus point is that if there is a grid outage then you have power, for a day or so if you are careful.
- Grid attached with solar/wind: as above, but you can charge independently from the sun/wind... obviously in some places (like the UK) this has limited utility because the sun don't shine (like today), and the wind can be annoying and difficult as a power source (gearboxes, noise, aesthetics). Can cost in though - because of summer power my panels pay back in 11 years. Small wind turbines seem to be getting more practical but I am no expert.
- Non grid battery backup. These also come with solar now, so you can recharge if it's sunny. These are cheap (<~£1000), hold maybe 2Kw and so can power some devices while the grid is off for a little while. Definitely you can run your phones and computers for a few extra cycles, but people are often looking to run freezers or fridges with medicine with these.
Another thing that folks like to have is grid independent heating / cooking via a woodstove. This is frowned on in urban areas and by eco people but I live in the country and have done my reading and while other people will pop up and decry particulates to be honest I'm keeping my burner so my family will be warm and fed for as long as our food lasts or we don't get looted by the neighbours.
Makes sense, but still can't imagine a post apocalyptic world and how I'll live without power :(
212MB for MacOS and 25MB for Windows? Why are MacOS binaries so large? Is it typical for them to be 10x Windows binary size?
That said, I'm really looking forward to small and quick (latency wise) models are a reality. I can easily see a world where every keystroke, terminal command, etc. goes through a "autocorrect" type model. You could even blend natural language plus terminal program segments and the AI just infers what you intend. Either built-in or a second classifier model, determines if the autocorrect change needs human review first.
They bundle both python and ollama in that app bundle, and the ollama folder is something like 500MB unpacked , bundled python I think was 80MB.
Not sure what they do on the windows side.
Back in 2018 I was working on a project for educating schools in certain parts of Africa and Middle East, on AI. The issue was it had to be air-gapped (no internet guarantees) and small/portable. I ended up downloading Wikipedia (not all of it), and then created a lightweight inverted index (for search) and TextRank (for summaries). The whole thing was on a Raspberry Pi, and installed in a small plastic enclosure. We had many of these and could easily ship them. There was an "AI Learning Module" as well we built, that started with Scratch, and then moved into Python. But if I was to do it all over today, I would probably add a tiny LLM and maybe a small ASR and a TTS model too, and you basically have a completely self-contained AI knowledge assistant in a cigarette box. The point being, you basically also have a "survival AI" you can take with you. Of course you still need electricity...
That sounds fantastic and you could run it on a small solar panel and a big capacitor. Did you get any feedback about how it went in the field?
Great idea, I do a lot of work testing small LLM's in this space and agree if you add some guardrails and train a small embedder, you won't need these large models, as your info is static, you can ship it all as one.
Or try these with your trained embedder: https://ollama.com/library/minicpm-v4.6 https://ollama.com/library/bonsai-2
A detail from the benchmarks in that page is that Nemotron Lightning has good results for a MoE model close to Qwen 27B which is dense. Very interesting considering that Qwen 35B MoE stopped being in Alibaba's plans, and curious if Nemotron is equally capable in other bemchmarks.
How are we powering this computer? Maybe be need a bootstrap llm that can answer only that question and runs on a solar device? Or some kinda clockwork bad boy, now you're talking :)
I went through a category 5 hurricane that took down everything. Prepared by downloading as much as I could ahead of time but it wasn’t enough. This, or something similar, would have been a blessing.
Love this. And as a trend, I'd love to see more local/small task-specific models/agents. Experts at helping you with that one thing, leaving the everything-and-the-kitchen-sink to the frontier models/agents
We need this, but running on smartphones.
Also, I am surprised that the difference between 32GB and 128GB in right answers is so small:
* Mac with 128 GB or more memory NVIDIA Nemotron 3.5 Super 21 of 22 right 80 GB
* Windows PC with 32 GB or more NVIDIA Nemotron 3.5 Lightning 19 of 22 right 25 GB
I like to use llamafile for cases like this: https://github.com/mozilla-ai/llamafile
I made it a while ago now, but similar: https://github.com/x3haloed/eowkit
Helps you download a local LLM and offline Wikipedia. Probably easier to just ask your favorite agent to glue something together yourself these days.
I like how both these projects seem to imply that in the event of an EOW scenario linux users can just f##k right off, thank you very much. xD
I saw emergency and I immediately thought in case I couldn't access online docs or get my coding/platform questions answered day-to-day.
Apocalypse emergency I don't need help on. My crisis brain has collected more than enough info and capabilities over the decades.
Really cool idea! Will give it a spin.
I’m currently using https://kiwix.org for the offline access to Wikipedia, but your Survival LLM looks even better.
At what point would it be better to download a few real sources and do plain text search? Why risk a hallucination for content that would probably be smaller than the size of the model?!
this is more like .. survival harness, no?
>The app is the same everywhere. When it opens, it checks your computer's memory and downloads the AI model that fits. More memory means a smarter model.
first thing an emergency tool should require, internet access.
at first glance I figured it'd be an ultra small specialty trained survival model that'd be small and runnable anywhere, sorta like an emergency flavored version of those tiny tts models that have been all over recently.
Maybe that's an idea for someone.
This could be made a lot more practical (and safer) if made searchable via a simple vector search / embedding that can run on any ordinary computer.
The source (data collection) seems the most important feature here worth reusing.
What this needs is a recipe or script that you can point your local agent at and it builds a bespoke implementation that’s, by definition, highly resilient.
Edit: see project nomad.
Sorry if this is a dump question but I was wondering why not fine tuning each model to get 100% accuracy on those topics?
Alternate idea: Download Unsloth Studio https://unsloth.ai/docs/new/studio#quickstart
From the command line: unsloth studio
Browse to the URL it gives you (eg http://127.0.0.1:8888/)
Download a good fast local model e.g. Gemma-4-12B (small machine) or Qwen3.6-35B-A3B (larger memory). Or a Nemotron model, if you prefer that.
Then you'll have both your backup/emergency assistant that runs on your own computer and be gaining skills in a common, frequently-updated, well-supported program.
Wonder why they didn’t run Qwen 3.5 9b on 16th Macs. That’s a super impressive model for size. Is granite better?
I am not going to accuse anyone of anything, but this looks suspiciously like the project I have been working on. The dates, the time, the folder structure, the concept. It is a bit disheartening, because it missed the whole point, and it butchered the implementation. No LLM makes sense. Having an LLM in the loop is having the worst of both worlds? Example: My initial use case was to provide schools and traders in rural Africa with at least some sort of free LLM-like capability. They have phones that cost $5. Power cuts, drop of the cellular network. Not just 'No-LLM to prove a point'.
It is also only 5% of the wider scope and I was about to release it under OSS 2 days ago, but wanted add some final finess. Now that this is out, I might as well release it so the concept actually ties to its original goal, and release the scientific papers that date back to Feb. Please ping me on github. Same username as here. Always could do with help.
Odd that it doesn’t run on phones. It isn’t that large, 212MB on a Mac. Phones are basically everyone’s EDC and most are quite powerful.
That’s just the size of the app. It then downloads the appropriate model given the specs of the machine.
LLM-authored website convinces you to waste time and energy on chatting with an LLM when struggling to survive.
With all due respect: why does this need an LLM, and this much data? Surely a "classic" knowledge base with a more traditional search bar, running on top of the same data this LLM was trained on would be way smaller, and actually as trustworthy as the source material it surfaces for you?
There are a fair number of people who seem to believe that LLMs contain "world knowledge" and are blissfully unaware of how inaccurate an ungrounded chatbot can be. They ask it questions, it gives them confident and plausible (sometimes even correct!) answers, and they leap to the conclusion that these are useful tools for end-of-civilization knowledge bases. I fought this battle countless times on HN and Reddit, generally unsuccessfully.
This project at least attempts to ground its answers with (presumably) human-vetted sources. That will make it much, MUCH more accurate and truthful than a bare model. But there is still a non-zero chance for it to hallucinate answers, especially when posed a question that it doesn't have any source material in its database.
As for why bother hooking up an LLM instead of a simple search engine, search engines don't synthesize data from multiple sources into a coherent answer for you, but LLMs are (mostly) great at that.
That said, while I like this pattern (LLM + knowledge base) for lots of things, this isn't necessarily something I'd trust with my own (or my family's) survival.
Yeah, without the ability to search the web, a very small model is going to be too dumb to be useful, and maybe even dangerous due to hallucinations. But, there is a point where the knowledge of self-hostable models will surprise you. That point is probably not runnable on the average laptop, though. It's maybe in the ~30B range, but more realistically in the 128B MoE range. I guess in their tests Qwen 3.8 27B got as many right as the much larger Nemotron Super, but I'd bet Qwen 3.8 Flash would be better than either, but it needs 128GB of unified RAM or a big GPU and lots of system RAM to run the 4-bit version.
I think if I had to build an emergency LLM today, that had to run on modest hardware, I'd bet on Gemma 4 12B. It's got excellent reasoning and good vision/audio and speaks 140 languages.
But, I don't know about the "classic" knowledge base theory, though. Is there a high quality curated pile of survival information that could be bundled into a web UI and made searchable in a knowledge base? The LLMs aren't focused on that topic, so there's a lot of wasted space, but they know a little about a lot of things, including survival topics. Combined with Wikipedia, and maybe a few other sources, you're probably better off with one than without.
I guess one could use some huge models plus web search to compile/distill a focused survival knowledge base or LLM.
Edit: Project NOMAD seems to mostly be exactly that. It has authoritative sources in a searchable knowledge base and the tiny LLMs are an afterthought, which is probably what they should be. https://www.projectnomad.us/
The only way Big AI labs will sell us appliances is when the internet was somehow destroyed.
Not sure where this would fit in.
Qwen 3.8 27B runs well on my laptop. And I can fit terabytes of human knowledge on it.
pretty cool I like it. could you support more (small) models in the future, e.g. from the qwen or gemma family?
Nice idea! I wonder how the installed IBM Granite 4.2 8B LLM does on machines with "modest" RAM
When I quit the app, why is it still running in the background?
Can this work with ollama?
On the setup process: "You only click for about 5 minutes; the rest is downloading." On the energy consumption: "A small generator or power station runs it easily"
Five minutes of clicking and a (small) power station is a small price to pay when survival could be at stake.
Bold of you to assume there will be running computers past the nuclear apocalypse. It is much, much more likely that a lot of electronics will be permanently fried by the inevitable EMPs. Distributing practical skills in how to survive is much more useful.
Seems like a remarkably stupid idea as opposed to just having an extensive encyclopedia downloaded with a very thin client you can use to read from it.
In an actual survival scenario power isn't guaranteed and errors of any kind can be life or death. So you need to minimize the resources used to get the thing working.
From the site:
>Survival LLM >It Can be wrong
thank you!
Have you considered just having a library?
I'd want an Android version...
LLMs have become the software equivalent of using a hammer to solve all your problems. Like others have said, there are much better solutions to provide an enhanced search engine for your survival knowledge.
I recently evaluated LLMs for use for offline navigation, with this very kind of survival scenario in mind: https://fig.blue/posts/directions-from-memory/
tl;dr: Local LLMs are really really bad at offline navigation.
That said, pairing the survival guide with a library is totally the right move.
Why would you want LLM navigation where offline deterministic navigation have been there forever?
If you happen to have an app and library of all the maps you want then yes, that is better. You could ask the same about Survival LLM: Why not just grep a survival guide?
The thesis is that someday an LLM might perform better than both. But I agree, not yet.
A survival guide won't answer a question, you need to search it for some sort of keywords, you might not be using the same term or not know what a particular thing is called, and might end up having to read all of it to find the info you need, or not find it at all.
Navigation is a closed task, A* will always find an optimal route as long as your street info is current, you can't do better than that.
it would be useful if it would shrink a little bit
It's disappointing that Gemma E4B seems to perform poorly on this (42% accuracy according to the GitHub). It would be nice if a $25 phone could be loaded up with this and stuffed in a EMP proof metal box with a small solar charger. Maybe a finetune or Gemma 5 will get us there.
"Survival LLM, the power is out and there's no food, how do I turn your computer on to ask your questions?"
Just few days ago I thought digital preppers are soon gonna make something like that. It's a generally good idea.
I'd put in this also a ton of software documentation, minimally for Rust.
And a bunch of scientific literature.
I can almost guarantee you that by the time you need a survival assistant, you won't be willing to spend gasoline on generating electricity for your GPUs.
(It's helpful for shorter outages. But "survival assistant", I think not, unless you run a compound)
Talos Principle vibes.
This will come in handy after AI takes over the world.
But kidding aside, this is an interesting reveal on the ease with which a custom LLM can be spun up to fit a particular niche application, especially for systems not meant to host an LLM.
If you're actually offline and need information in a 'survival' situation, I'm not so sure the hallucinatory nature of an LLM is the based way to distribute a repository of information. Additionally, there's no need to fit an LLM entirely in memory.
In a theoretical scenario where the internet is gone and isn't coming back: If you can deal with a very low token/second rate there's no reason not to store 'offline' a much larger model like qwen 3.8-flash-next or deepseek v4 flash 1017 and use an inference engine which can stream-read it off disk to extract the information you want, albeit slowly. Of course also download and use things that'll fit in RAM, sure, like the qwen 3.8 27B in the linked page. But no need to restrict yourself to only smaller models.
if your computer doesnt work during an emergency because power went out, how will your LLM work?
No GNU/Linux? Meh.
Agreed. Especially for something like this, in which many imaginable situations would require the ability to run on Linux rather than MacOS or Windows, pretty strange.
How on earth are you going to operate this if you have no electricity?
What are generators and solar panels? Come on.
This is just crap. Why would you want something that can give you wrong answers (like 4 out of 20 like in the tables, that is much!) - in an emergency?
Please, please do not trust a chatbot in emergencies. There’s a reason why actual survival and emergency preparedness guides include manuals rather than recommend you just use a chatbot: practicality.
Just look at those specs needed for accurate-ish results. You really think your 128GB Mac Studio or Framework desktop is going to be able to work in a real emergency situation? Even if it is, how long will it last? What about those precious seconds waiting for inference?
The danger here is less hallucinations and more, well, everything else about it. Instead of setting this up, take the time to make sure you have a restocked first aid kit and enough water for a week of use by your household. Stock up on meds and non-perishable food. Plan exit strategies and contingencies. Acquire and store little first aid booklets or manuals of common survival tasks in physical form (or hell, throw onto an eReader - infinitely more battery life than an LLM host in an emergency).
This is one of those “sounds good in my head” projects that folks with emergency experience would bristle at. This is a hindrance, not a helper.
No thanks, I'll use a generic model along with trusted sources.
Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
You can always not comment.
Not paying the $100 annual extortion fee doesn't make you inexperienced.
The irony is thick. The dev is paying Anthropic $200 a month, but $100 a year for code-signing is extortion.
The $100 merely serves as a gatekeeper to prevent people and non-devs to create unlimited developer accounts. It used to be $500 a decade or two ago, and it was worth it even back then, until Apple realized they should probably just give it away almost for free.
> Also: "Apple could not verify “Survival LLM” is free of malware that may harm your Mac or compromise your privacy." This is obviously some vibe coded trash from an inexperienced dev.
This is a great example of how Apple's "scare warnings" completely work to mislead folks about what they are actually warning you about.
Code signing and sandboxing exists for a very good reasons (security and privacy) and it's easy enough to ship a sandboxed app.