Qwen3.8-27B-MTP-mxfp8
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This model was converted to MLX format from `Qwen/Qwen3.8-27B` using mlx-vlm version **0.6.8**. Refer to the original model card for more details on the model.
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> **Built with mlx-optiq**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. Try the Lab · All OptiQ quants · Docs A 4-bit mixed-precision MLX quant of Qwen/Qwen3.8-27B, an image+text model. Per-layer bit-widths come from a KL-divergence sensitivity pass on a six-domain calibration mix (prose · reasoning · code · agent · tool-call · constraint-bearing instructions). Sensitive layers go to 8-bit; robust ones stay at 4-bit. The vision tower is kept at bf16 in a sidecar, so this repo loads text-only under stock `mlx-lm` and image+text under OptiQ.
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> **Built with mlx-optiq**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. All OptiQ quants · Docs OptiQ mixed-precision quant of orcarouter/Qwen3.8-27B-Uncensored, a Qwen3.8-family reasoning model with a bundled MTP speculation head. 19 GB on disk. Following the naming `llama.cpp` uses for its mixed quants, the "4bit" label denotes the family, not the weighted average.
4-bit MLX conversion of Qwen/Qwen3.8-Flash-Next, converted with `mlx-vlm` `main` (post-#2032) at commit `d1bd74ed`, group size 32. `Qwen4ExpRMSNorm` applies `1 + w` to norm gains that the released checkpoint stores centered at zero, matching upstream `Qwen4ExpTextRMSNorm`. Several MLX conversions published before #2032 landed were made with a converter that folded that `+1` into the saved weights, so loading them applies the offset twice and generation degenerates into noise (#2041). A gain center near `+1.15` instead of `+0.22` is the signature of the double-shifted conversions described above.
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This model mlx-community/Qwen3-8B-4bit was converted to MLX format from Qwen/Qwen3-8B using mlx-lm version **0.24.0**.
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