One signal

Update

What changed

Unsloth’s release notes give a further performance detail for Recursive’s Flint coding-agent model: they report a SWE-bench Pro v2 score of 89.7, compared with 73.8 for Qwen 3.6. The figures are Unsloth’s, and the notes do not establish an independent comparison.

The notes also say NVIDIA’s Gemma Nemotron 4B reasoning fine-tune beat the original Gemma 4 E4B on 16 of 21 NVIDIA tests, with its largest gains in tool use and multi-turn chat. For Windows and Linux users, Unsloth adds REAP expert pruning, which can remove 25% or 50% of a mixture-of-experts model’s least useful experts, with some quality cost.

For training workloads on NVIDIA Ampere or newer, Unsloth reports that DPO and other training that pads sequences run up to 3.8 times faster with less memory. These are specific claims in the project’s release notes, not independent benchmark results.

Sources and evidence

• Releases · unslothai/unsloth · GitHub: Unsloth’s v0.1.910 beta release notes report additional model benchmark results, expert-pruning support and faster training for specified workloads.

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