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zaydiscold/Qwen2.5-7B-Instruct-MLX-8bit
Qwen2.5-7B-Instruct-MLX-8bit is a machine learning model from zaydiscold. Use it for the machine learning 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 apache-2.0.
MLX 8-bit conversion of Qwen/Qwen2.5-7B-Instruct. Default group size (64).
Downloads · 30 days
7
7% of all-time downloads
All-time downloads
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7.6B
8.1 GB on disk
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.safetensors8.1 GB · 100%
How the weights are stored.
U327.6B · 100%
From the Hugging Face model README
MLX 8-bit conversion of Qwen/Qwen2.5-7B-Instruct. Default group size (64).
Converted directly from the original HF bf16 safetensors.
| Variant | Repo | Disk | ~Min unified RAM | Role |
|---|---|---|---|---|
| MLX bf16 | Qwen2.5-7B-Instruct-MLX-bf16 | 15.24 GB | ~18 GB | Reference |
| MLX 8bit (this repo) | this | 8.1 GB | ~10 GB | Near-lossless |
| MLX 6bit | Qwen2.5-7B-Instruct-MLX-6bit | 6.2 GB | ~8 GB | Quality / size middle |
| MLX 4bit-gs32 | Qwen2.5-7B-Instruct-MLX-4bit-gs32 | 4.77 GB | ~7 GB | 4-bit, group size 32 |
| MLX 4bit-gs64 | Qwen2.5-7B-Instruct-MLX-4bit-gs64 | 4.3 GB | ~6 GB | 4-bit, group size 64 (mlx-lm default) |
| MLX 4bit-gs128 | Qwen2.5-7B-Instruct-MLX-4bit-gs128 | 4.06 GB | ~6 GB | 4-bit, group size 128 |
| MLX 3bit | Qwen2.5-7B-Instruct-MLX-3bit | 3.34 GB | ~5 GB | Smaller, expect quality drop |
| MLX 2bit | Qwen2.5-7B-Instruct-MLX-2bit | 2.39 GB | ~4 GB | Aggressive — verify on workload |
Collection: Qwen2.5-7B-Instruct MLX ladder + group-size sweep
pip install mlx-lm
mlx_lm.generate --model zaydiscold/Qwen2.5-7B-Instruct-MLX-8bit \
--prompt "Explain quantum entanglement in one paragraph" --max-tokens 200
python -m mlx_lm convert \
--hf-path Qwen/Qwen2.5-7B-Instruct \
--mlx-path ./Qwen2.5-7B-Instruct-MLX-8bit \
-q --q-bits 8
Q4_K_M is llama.cpp; MLX has no literal Q4_K_M.