cturan/tony_nnue

The data here seems good enough on its own to train a pretty strong NNUE. In my own tests it did a good job of pulling draws out of Stockfish :P To keep costs down, it was relabeled with t1-256x10-rl-base-swa-3860000, and most of the self-play games were also generated with that same model, in a single pass with a bit of temperature. Bigger lc0 models would be far more effective, but this one hit around 660k/s on 8× 5090s, which made it cheap, so that's what I went with.

<iframe src="https://silytics.si/embed/item/3555979c-7c8d-40a1-87a8-65346f0168dc" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 19 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.