DeepSeek V4.1 Flash is positioned as the smallest member of a new architecture family designed for higher capability ceilings, faster inference, greater throughput, and clean scaling to larger models. It ships as an open-weight release under an MIT license, with a Mixture-of-Experts design totaling 763.2 billion parameters trained on 45.0 trillion tokens, giving it a 59x tokens-to-parameters ratio. Native multimodal visual understanding is built directly into the architecture, so the same checkpoint can accept both text and image inputs and is intended to be a unified foundation for reasoning, coding, and agent workflows rather than a vision add-on.
In practice, the model leans into agentic and coding tasks. It ranks first on Codeforces-style competitive programming with a rating of 3471 and first on Terminal-Bench 2.1 at 0.91 in the cataloged API limit context, while also leading the BabyVision early visual reasoning benchmark at 0.90. Reported reasoning and knowledge scores include GPQA Diamond at 0.91, MathArena Apex at 65.6, and HLE at 36.8, rising to 63.9 when tools are enabled on the pure-text subset. Strong agent results such as DeepSWE v1.1 at 74.2, NL2Repo-Bench at 65.4, CyberGym at 88.1, and SEC-Bench Pro at 62.8, together with top-tier vision performance, make DeepSeek V4.1 Flash a practical fit for long-horizon coding agents, tool-using assistants, and multimodal pipelines that benefit from a self-hostable open-weight checkpoint.
