GoKawiilDeepSeek releases V4.1 Flash 1017, its first CED-architecture model
DeepSeek has shipped V4.1 Flash 1017, dated October 17, 2026, as a snapshot of its V4.1 Flash model available via the deepseek-flash API. The sparse mixture-of-experts model uses a new Causal Encoder-Decoder architecture, activating 8B parameters on input and 16B on output from a 552B-parameter backbone, with native image understanding trained jointly with text from the start.
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The asymmetric compute split and compressed KV caching, which DeepSeek says cuts cache memory to about a quarter of the prior Flash generation, point toward a strategy of lowering costs for agentic and long-context workloads rather than maximizing raw capability. DeepSeek's own claim that it beats V4 Pro on performance, speed, and task completion time suggests the company is positioning Flash as the economical option for sustained multi-step tasks like coding and computer-use agents, though these comparisons come from DeepSeek itself.
- V4.1 Flash 1017 introduces DeepSeek's first Causal Encoder-Decoder architecture with an 8B/16B input/output parameter split from a 552B backbone
- Compressed KV caching reportedly cuts cache memory to about a quarter of the previous Flash generation, lowering agentic workload costs
- DeepSeek claims the model outperforms V4 Pro on performance, speed, and task completion time while serving as the cheaper tier of the V4.1 family
Source: openrouter.ai, 2026-10-17
Published there as: “DeepSeek: DeepSeek v4.1 Flash 1017”
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