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npario/Swift-Qwen3.8-27B-MLX-MXFP4
Swift-Qwen3.8-27B-MLX-MXFP4 is a image-text-to-text model from npario. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as other.
MLX MXFP4 (mxfp4, group size 32) quantized variant of ukisai/Swift-Qwen3.8-27b (text tower quantized; vision tower and projector retained in BF16) for Apple silicon via mlx-lm.
Downloads · 30 days
155
49% of all-time downloads
All-time downloads
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27.4B
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.safetensors15.2 GB · 100%
How the weights are stored.
U3226.9B · 98%
From the Hugging Face model README
MLX MXFP4 (mxfp4, group size 32) quantized variant of ukisai/Swift-Qwen3.8-27b (text tower quantized; vision tower and projector retained in BF16) for Apple silicon via mlx-lm.
048328f4059015b63f860a453bf94834af0db683 (Swift Open License v1.0 for the UkisAI contribution + Apache-2.0 for the Qwen base (upstream LICENSE, LICENSE-APACHE-2.0, NOTICE)).mlx_lm.convert (mlx-lm 0.31.3): mxfp4,
4-bit, group size 32.Before upload this pack passed a deterministic coherence gate: greedy
48-token chat generation loaded through
mlx_lm.load, judged for emptiness, repetition loops, multi-script
gibberish, and special-token debris. Verdict: ok.
pip install mlx-lm
mlx_lm.generate --model majentik/Swift-Qwen3.8-27B-MLX-MXFP4 --prompt "Hello"
Coherence smoke gate only at publish time (see Smoke gate above). Per-tier gate records live in majentik/garden-quant-bench; perplexity / benchmark rows are added here when measured.
This pack is a quantized (Object-form) redistribution of ukisai/Swift-Qwen3.8-27b and inherits its dual
licensing unchanged:
LICENSE-APACHE-2.0);LICENSE),
which is free for research and commercial use by organisations with up to US$1M gross annual
revenue; larger organisations need a Swift Enterprise License from UkisAI.LICENSE, LICENSE-APACHE-2.0 and NOTICE are shipped verbatim in this repository as required by
Section 4 (Redistribution) of the Swift Open License. The only change from upstream is the MLX
quantization described above.