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You can try 7 different tiny LLM's in your browser.
What I missed from the title was this: Can I try 7 different tiny LLMs in my browser?
i have a bromine tub, give me simple instructions for what to do since i just filled it up w fresh water
1. Add 1 tablespoon of water to the water bath. 2. Place the tub into the water bath and let it sit for about 5 minutes. 3. After 5 minutes, remove the tub and let it cool down. 4. Now, fill the tub with water and let it sit for about
uhmm completely unusable ?
No, that is not what SLMs are useful for. They have very little knowledge, and typically lack reasoning skills.
Useful applications include sentiment analysis, text classification, entity extraction, etc.
They certainly can be useful, but you shouldn't compare them with LLMs such as Opus or Fable.
Completely unusable for that, yeah, that's a 100M model, not an assistant
The website literally says they are SLM's .. derp af
I did the default arithmetic with PetitGPT research-v1
Answer
Brilliant
That's not incorrect.
LLMs produce semantically correct sentences, not factually correct statements. Have we forgotten this so soon?
It is, in every sense, incorrect. Which statement in this short snippet is "semantically correct"? (Better LLMs get this right, of course.)
It's not very good semantically either.
I got the correct output for PetitGPT research-v1: https://ibb.co/0pP9DS2T
GPT-2 124M is terrible...
Answer:
It's not instruct tuned looks like? It's closer to a base model rather than a chatbot.
That one is a 2019 model :) Years before the ChatGPT public preview.
GPT-2 is an interesting one because it is a February 2019 model. (You can see some information about it below the card if you click on the card.)
That was 2-3 years before the big "ChatGPT moment" (the highly coherent ChatGPT research preview was released in November 2022, I think it was ChatGPT 3.5). Back in 2019 the models really were not producing very coherent output. Now you can see it for yourself right in your browser :) Everything has come a really long way since then!
I built something like this just last month, using a few of the same models, but I used ThreeJS's Three-Shading-Language abstraction to do it: https://three-llm.ben3d.ca/?model=qwen3.5-0.8b
Awesome! I tried it and after loading (which took a while as it is a large model) got 12 tokens/second and very coherent output. Great demonstration.
Similarly, if someone wants to hack some LLMs in their browser and burn some cycles, please feel free to try to break them here:
https://ai-attacks.neal.codes/
Cool project, but I'd really suggest looking at the UI.
The text is too small and it's way too dense with information in general. Considering how simple this product is to use, it's kinda crazy that I have to scroll through over a page length of (mostly useless, AI-generated) information before getting to the actual interface.
Also what is going on with the footer (why does it link back to the site itself, why is it telling me to "serve over HTTP").
This is the future of software, sloppy ui.
Thank you for the feedback, I'll think about how to incorporate the changes you've suggested.
Wouldn't that be a TLM?
I have been experimenting with something similar here - https://sonistellar.com/lab/
PetitGPT told me that
Otherwise, a very neat demo. As others have said, the UI is VERY confusing, way too much stuff going on.
It is. For very small values of 2.
Really cool project. Giving web apps direct access to on-device models is something I’m excited about, and it’s cool to see the different approaches.
I’ve been working on a related proposal called the Web Models API, which explores a browser standard for an API that runs open-weight models on-device. Would love your thoughts: https://www.webmodels.dev
I read your proposal, I think it's great! Where will the navigator get the model if the user agrees to download it? For this demonstration I just serve the models on my own server, but for larger models it may be an issue as they may not have direct download links even if they are open weights.
Great question. Right now there isn’t a definitive answer, but it’s something that needs to be worked out. There would likely be a registry. The question is how to keep model IDs consistent: does each browser manage its own registry, or is there one shared across browsers?
Since you're asking for some kinds of permissions anyway, you could ask if the user is willing to also seed the model, p2p. (However, seeding files is not as popular as it used to be, many residential Internet connections don't have good upload.) If you have the capacity for it, your site webmodels.dev could act as a tracker and initial seed for any models. Then it could be the one central registry. It might get to be too much for you though, a lot of the open weights models are huge.
Interesting idea. I hadn't considered that. Thanks
unfortunately on firefox: Uncaught ReferenceError: GPUShaderStage is not defined
I tested it on Firefox on windows, version 156.0.1 and didn't get that error.
What version of Firefox are you using and what is your operating system and graphics card, please? Can you also try it without WebGPU? (Reload the page and uncheck "Prefer WebGPU" and try a prompt.)
I like it as I'm vibecoding an (airgappable) browser AI workspace myself, but in terms of putting the models to use, just exposing the chat interface feels a bit limiting to me.
My take on this concept: https://github.com/willaaam/gemma-4-E2B-webgpu-vision
It's a cool project, but I couldn't get it to load. What did you test this on? I tried the live link here:
https://willaaam.github.io/gemma-4-E2B-webgpu-vision/
And after loading it, with an NVidia 1060 GPU (6 GB RAM) on Windows it failed with "Failed to load: No supported WebGPU variant for com.xenova.gemma4.DenseGemv; rejected sgma".
In Safari on a 2026 Mac Mini M4 with 24 GB of RAM it failed with "Failed to load: JSON Parse error: Unexpected EOF".
The idea is pretty cool though!
Nothing on this site actually works.
What browser are you using? I tested it on Windows, Mac, and iPhone. I tested it in Chrome, Firefox, Edge, and Safari. Everything works on the three machines and phone I tested it on.
(It's a little bit slow at the moment - you have to wait a few seconds for the models to load - as it's currently on the HN front page. The server is on a 1 gigabit unmetered network connection so it can serve all the weights - around 600 megabytes - to one person every few seconds, there are several concurrent users now.)
serve the models via CDN?
I think that tells you all you need to know.
It's LLMs, not LLM's ;-)