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Someone squeezed a Qwen3.8-27B fine-tune down to ~7.4GiB on the GPU. Not sure I believe…

Someone squeezed a Qwen3.8-27B fine-tune down to ~7.4GiB on the GPU. Not sure I believe it. And somehow it just scored…

This is a dev post classified by AGK Intelligence as AI dev tools (a tool drop), kept by the Dev Radar because it carries real work, not commentary.

Someone squeezed a Qwen3.8-27B fine-tune down to ~7.4GiB on the GPU. Not sure I believe it. And somehow it just scored higher than Qwen3.6-27B BF16 on LiveCodeBench. 👀 The new Swift 1.5 / Qwen3.8-27B ATX AI2 build is only ~2.3 bits per weight. Stats 💾 ~7.4GiB resident on GPU incl. MTP 🧠 27B parameters ⚡ >90 t/s reported for agent work on 3090/3080 Ti 📚 designed to make 200K+ context possible on 12GB Ampere cards ⚙️ custom llamAmpere runtime This is almost unbelievable. LiveCodeBench v6: Qwen3.8 27B 2.3bpw → 84.3% Qwen3.6 27B BF16 → 83.9% Qwen3.8 27B BF16 → 90.3% So no, the 2.3-bit model

Posted by David Hendrickson (12.6k followers) 1 h ago · 6 likes · 469 views · view the original post on X. Kept by the Dev Radar as AI dev tools.

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Every post is read and classified by AGK Intelligence: what it is, which market it belongs to, and whether the link is a real tool. 31.3k posts from 5k X accounts over the last 21 days, 9.1k tools, 12 markets. New posts are collected several times an hour and the full ranking is recomputed every hour — last update 2026-11-02 21:22 UTC. Full method.