FINE-TUNING

A Huawei-Queen's study finds open coding models fine-tuned under OpenHands degrade sharply under other scaffolds - SWE-Lego-Qwen3-32B drops from 52.6% to 8.4% Pass@1 on OpenCode. The fix: train planning as a model capability, not a scaffold artifact.

FermiSense fine-tuned Qwen 3.5 9B with 2,500 GRPO steps on a single GPU for $500 and beat GPT-5.6 Sol (93%) and Opus 4.8 (91%) on automotive catalog review, reaching 97% accuracy at 68x lower cost per listing.

Gemma 4 ships byte-for-byte open weights from Google DeepMind. How developers deploy it locally, fine-tune it, and ship agents on top of it.

Meta's open-source model family. Llama 4 available in Scout (17B active) and Maverick (17B active, 128 experts). Free to use, modify, and deploy commercially.