An open System One model, with the data already collected.
Cuth
@ItsCuthulhu
Now that I've collected so much data on System One models on my DGX Spark. Lets see if I can beat Jev on size, speed, and accuracy.
It will be MIT for anybody to build on. Everything I do on here is open source.
Cuth has collected a lot of data on System One models on his DGX Spark and now wants to try to beat Jev on size, speed and accuracy. He says it will be MIT licensed and open source.
you can make any open source model behave like jev with just a bit of inference engineering.
it's shockingly easy. to prove it, we built a new endpoint we're calling deepseek-v4.1-flash-jev. see the demo below. here's how it's done:
sglang (an inference engine) offers a scoring endpoint in addition to the normal generation one. in scoring mode, given an input & set of possible answers, it forces the model to produce probabilities for each one. example:
> input: what is most common letter in abcccde?
> possible answers: a, b, c
> output: (c, 0.9), (b, 0.0.5), (a, 0.05)
getting the above behavior instead of streamed output is as simple as using sglang's /v1/score endpoint instead of /generate. there's just one other trick required.
for deepseek, you have to add a closing think tag before the response. this forces a direct answer instead of a reasoning trace. if you want reasoning, you can do that too, but imo that makes things too slow to be worth it.
dsv4.1 flash is not as good as jev, but if we had enough spare compute to experiment with this same approach for a larger model then i think the decision quality would be at least as good, if not better.
also, somewhat unrelated, i think decision-making models kill all prospecting & sourcing work. i would have absolutely killed to have jev or similar when i was recruiting @mintlify. absolutely incredible.
