DeepSeek-V4.1-Flash
MultimodalDeepSeek-V4.1-Flash is DeepSeek's open-weights multimodal Mixture-of-Experts release of September 2026. Its 552B-parameter backbone activates 8B parameters per token during prefill and 16B during decode, and it supports up to 1M tokens of context. The architecture pairs a 20-layer causal encoder with a 20-layer decoder, Compressed Sparse Attention 2 with a Hierarchical Sparse Indexer, an FP4 main KV cache (about 890 bytes per token), SWA Bounded Replay, Single-Pass mHC and Engram conditional memory (196B parameters), plus DSpark speculative decoding. It accepts native image input through DeepSeek-ViT and was pretrained from scratch on a 45T-token multimodal corpus with reasoning effort continuously controllable from 1 to 100.
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Compare DeepSeek-V4.1-Flash
All comparisonsArticles about DeepSeek-V4.1-Flash

DeepSeek V4.1 Flash tops AA's new agentic benchmark by 0.4 points. The index under it moved twice in a week
An open-weights model took the top row of Artificial Analysis's new private agentic benchmark by 0.4 points, on an index revised twice in just three days.

A 510GB model called Flash: the local-hardware reality of DeepSeek V4.1-Flash
DeepSeek's Flash model weighs 510GB, but local-inference readers argue only about 150GB must stay resident, because the Engram table is looked up, not streamed.

DeepSeek V4.1 Flash vs GPT-6 Astra: 98% of the score, 1.4% of the cost
Arena-measured data put DeepSeek V4.1 Flash within two points of GPT-6 Astra on design output at 1.4% of the cost, and the ranking flips once speed is weighted.

DeepSeek V4.1-Flash ships open weights built around a smaller KV cache
DeepSeek published V4.1-Flash open weights on Sept 10: a 552B multimodal MoE with an 890-byte KV cache per token, and vendor numbers that show where it loses.
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