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The Model mlx-community/DeepSeek-R1-Distill-Qwen-32B-4bit was converted to MLX format from deepseek-ai/DeepSeek-R1-Distill-Qwen-32B using mlx-lm version **0.20.2**.
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This model was quantized using oQ (oMLX v0.7.1) mixed-precision quantization with Improved oQe Quantization (jundot/omlx#4385). A mixed-precision MLX checkpoint of deepseek-ai/DeepSeek-V4.1-Flash-1017, a minor update to DeepSeek-V4.1-Flash with improved reasoning, coding, agentic and visual performance. It is a multimodal mixture-of-experts model with 552B backbone parameters, a Causal Encoder-Decoder layout, Compressed Sparse Attention 2 (CSA2), Engram conditional memory and DSpark speculative decoding. It includes the language model, the Engram tables, the vision encoder, the multimodal aligner and the DSpark MTP weights. The effective average is 4.365 bits/weight excluding the Engram tables, or 4.529 bits/weight for the complete checkpoint.
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DeepSeek-V4-Flash-2bit-DQ uses a dynamic mixed-precision quantization policy. Most routed MoE expert weights are packed to 2-bit, while sensitive layers and projections remain in higher-quality 4-bit, 6-bit or 8-bit quantization. This keeps memory use much lower than the baseline 4-bit checkpoint.
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