DeepSeek-V4.1-Flash-1017-oQ3e-mtp

DeepSeek-V4.1-Flash-1017-oQ3e-mtp#

Note. Updated 2026-10-29: Attention and indexer projections now use 8 bits instead of 4 and 6 bits (+1.3 GB). Please re-download if you have an earlier copy.

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 3.648 bits/weight excluding the Engram tables, or 3.996 bits/weight for the complete checkpoint.

Quantization and Bit Distribution#

oQ3e allocates bits by measured layer sensitivity, then rounds each group with an importance matrix (1024 samples x 512 tokens) and a weighted least-squares refit of its scale and bias. Below oQ4, the Engram tables stay at 4 bits and are left out of the bit budget, because oMLX can serve them from SSD instead of memory.

Storage Breakdown#

License#

MIT, following the source model. See LICENSE.