https://swelljoe.com/post/will-it-mythos/: "Poor performer here, only found the one bug that almost every model found, despite its performance on other benchmarks being excellent for its size. […] It also performs poorly in a chat without tools, exhibiting an ehthusiasm for hallucination. I’m currently working on a replication of this with full tool access, including bash/Python, which may allow this model to be competitive."
It doesn't self-improve, that's a misleading headline.
As far as I can tell they trained it by running their own reinforcement learning on top of Qwen and Gemma 4 (not sure how they combined weights from both, or if they used Qwen as the basis and Gemma 4 to help train?) - so the "self-improving" is about their training process, not how you use the weights.
I think the 9b and 31b dense are Gemma models and the 35B-MoE, and 397B-MoE are Qwen models since these are model sizes covered by each of them respectively
Previously: https://news.ycombinator.com/item?id=48709744
https://swelljoe.com/post/will-it-mythos/: "Poor performer here, only found the one bug that almost every model found, despite its performance on other benchmarks being excellent for its size. […] It also performs poorly in a chat without tools, exhibiting an ehthusiasm for hallucination. I’m currently working on a replication of this with full tool access, including bash/Python, which may allow this model to be competitive."
These are simply benchmaxxed versions of either Qwen or Gemma 4.
Can anyone explain what’s the story here? Is this just a re-skinned qwen? Who is deepreinforce-ai and why isn’t this model listed on their website?
How does it self-improve, does the model change on disk - or just during a single context run it gets better?
It doesn't self-improve, that's a misleading headline.
As far as I can tell they trained it by running their own reinforcement learning on top of Qwen and Gemma 4 (not sure how they combined weights from both, or if they used Qwen as the basis and Gemma 4 to help train?) - so the "self-improving" is about their training process, not how you use the weights.
I think the 9b and 31b dense are Gemma models and the 35B-MoE, and 397B-MoE are Qwen models since these are model sizes covered by each of them respectively
Gotcha. That makes more sense. We ran the model to train the model -> “self-improving”.