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DeepSeek releases open-weight V4.1 Flash with lower inference costs

DeepSeek released DeepSeek-V4.1-Flash, a 552-billion-parameter mixture-of-experts model with 8 billion active parameters for input and 16 billion for output. The release adds native vision, a new causal encoder-decoder design, lower cache requirements, API access, and MIT-licensed weights.

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CURRENT ASSESSMENT · REVISION 1
TOWARD DOOM57confidence 87/100

Why it moved the index

Open weights, API availability, native vision, and reduced inference requirements broaden access to a capable agent-oriented model and increase competitive diffusion. Performance is based mainly on provider benchmarks, and the release does not itself demonstrate loss of control or a real-world incident.

Assessment history

  1. R1
    Toward 57 · confidence 87

    Adds DeepSeek's dated V4.1 Flash release with open weights, API deployment, native vision, and lower inference requirements.

    11 Sept 2026

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  1. DoomBench assesses “DeepSeek releases open-weight V4.1 Flash with lower inference costs” as evidence moving toward doom, with magnitude 57 and confidence 87 out of 100 in the competitive race category.

  2. The DoomBench assessment of “DeepSeek releases open-weight V4.1 Flash with lower inference costs” is based on reporting from DeepSeek and records the editorial rationale, source quality, attribution, and revision history.

  3. DoomBench summarizes “DeepSeek releases open-weight V4.1 Flash with lower inference costs” as follows: DeepSeek released DeepSeek-V4.1-Flash, a 552-billion-parameter mixture-of-experts model with 8 billion active parameters for input...

    https://www.doombench.com/news/deepseek-releases-open-weight-v4-1-flash-with-lower-inference-costs-2026-09-10