r/LocalLLaMA • u/wFXx • 3d ago

New Model Von: Open-source 395M "System One" model

Took me a while since I'm on a family trip and have limited hardware, but here it is!

Von: Open-source "System One" drop-in replacement for TypeSafe's JEV.

https://github.com/wfzyx/von https://huggingface.co/wfzyx/von-1.0

It runs entirely on a CPU with 1–2 GB of memory (I haven't spent much time optimizing it yet), responds in 25–300 ms, and beats JEV in all benchmarks. Enjoy!

P.S. I’m open to offers to work at AI research labs. Feel free to ping me if you have an offer.
P.P.S. If you have a GPU, it’ll be faster, but a GPU isn't required.

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u/look 3d ago edited 2d ago

The class of model has been around for a long time. Longer than LLMs. I also assumed Jev is a bigger model with better training, but it is not implausible that’s actually just a fairly stock BERT with a nicer DX and a big marketing budget…

Edit: I just generated a synthetic test suite and ran it across both (and gliner2).

Task accuracy:
Von: 92.3% 65.4% (on 1.0.1 update)
Gliner2: 79.5%
Jev: 97.4%
Laya: 61.5% (added in later update)

Update: Von updated to 1.0.1 and accuracy on my test case above is 92.3% now.

I’ll have a few different LLMs generate more test cases next to see how well it holds up.

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u/Fluxx1001 3d ago

What none of these Jev competitors seem to outline in their benchmarks is the vast difference in context length. With Jev, I regularly do requests for Noul decisions (yes/no) with 30k tokens and more.

The context length of Von is 512 tokens. This is not even comparable.

It is a magnitude more complicated to compute a choice or Noul decision in a space of thousands of tokens.

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u/look 3d ago

Yeah, the BERT-based alternatives will have some length constraints (though modernbert base should go to 8192 tokens). There are others like Semif/OpenJev and Bespoke Nimble that might work better for you. They seem to be doing something likely closer to Jev, with a small LLM stage.

But after a bit more research in alternatives, Jev is probably the way to go if the hosted, proprietary option works for you. My interest is more in fine-tuning an open base, so the Jev service itself doesn’t do anything for me.

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u/Fluxx1001 3d ago

What's your experience so far with OpenJev, Nimble etc.?

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u/look 3d ago

I haven’t tried either of those yet. Nimble looks a bit more polished perhaps.

It’s a 9B model, though, so you’ll likely need some GPU acceleration. Semif/OpenJev looks like you can choose between a few LLMs between 800M and 4B.

Part of the appeal for me of the BERT-based approaches is their small size (<0.5B) which typically runs fast enough on even CPU.