Qwopus3.6-35B-A3B-v1 MLX
Collection
Complete MLX quantization grid for Qwopus3.6-35B-A3B-v1 — bf16/8/6/4/3-bit, every quant converted directly from HF bf16. None chained. • 5 items • Updated
How to use zaydiscold/Qwopus3.6-35B-A3B-v1-MLX-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwopus3.6-35B-A3B-v1-MLX-6bit zaydiscold/Qwopus3.6-35B-A3B-v1-MLX-6bit
MLX 6-bit conversion of Jackrong/Qwopus3.6-35B-A3B-v1.
Converted directly from the original HF bf16 safetensors. Not from GGUF, not chained from another quant.
| Variant | Repo | Disk | ~Min unified RAM | Role |
|---|---|---|---|---|
| MLX bf16 | Qwopus3.6-35B-A3B-v1-MLX-bf16 |
69.3 GB | ~72 GB | Reference |
| MLX 8bit | Qwopus3.6-35B-A3B-v1-MLX-8bit |
36.8 GB | ~40 GB | Near-lossless |
| MLX 6bit (this repo) | this | 28.2 GB | ~32 GB | Quality / size middle |
| MLX 4bit | Qwopus3.6-35B-A3B-v1-MLX-4bit |
19.5 GB | ~22 GB | Standard daily-use tier |
| MLX 3bit | Qwopus3.6-35B-A3B-v1-MLX-3bit |
15.2 GB | ~18 GB | Smallest practical |
Collection: Qwopus3.6-35B-A3B-v1 MLX
pip install mlx-lm
mlx_lm.generate --model zaydiscold/Qwopus3.6-35B-A3B-v1-MLX-6bit \
--prompt "Explain quantum entanglement in one paragraph" --max-tokens 200
python -m mlx_lm convert \
--hf-path Jackrong/Qwopus3.6-35B-A3B-v1 \
--mlx-path ./Qwopus3.6-35B-A3B-v1-MLX-6bit \
-q --q-bits 6
Q4_K_M is a llama.cpp format. MLX has no literal Q4_K_M — MLX 4-bit is the practical peer at a different quantizer.6-bit
Base model
Qwen/Qwen3.6-35B-A3B