Great to hear that you are planning larger benchmarks! I am particularly interested in longer-running tasks with many steps and self-correction. Divergence is fine as long as the model can still solve the task, which Divergence-300 @32 does not measure.

The current benchmark suites that frontier AI labs use are probably a good fit, e.g.

https://z.ai/blog/glm-5.3#:~:text=Performance%20across%20com...

https://www.kimi.ai/ai-models/kimi-k3#:~:text=Performance%20...

https://www.anthropic.com/news/claude-opus-5

https://openai.com/index/gpt-5-6/

But guessing from your current benchmarks, I assume that you are severely compute-constrained. What is your time budget?