DeepSeek releases 305B V4-Flash-Vision-Exp under MIT license

DeepSeek published a 305B-parameter experimental multimodal model, DeepSeek-V4-Flash-Vision-Exp, to Hugging Face under an MIT license. It is the first vision model in the V4-Flash family, adding a vision encoder and aligner on top of the text model's DFlash attention, MoE, Hyper-Connections and DSpark forward path.

The model card is spare. Its lone evaluative sentence reads: "Compared to DeepSeek-V4-Flash-0731, DeepSeek-V4-Flash-Vision-Exp achieves substantial improvements on its multimodal agent capabilities, while maintaining comparable performance on text-only agent tasks."

The benchmark table puts Vision-Exp at 36.5 on ApexBench Pass@1, up from 26.2 for the text-only V4-Flash-0731 and shy of Opus-4.8's 39.4. Agents' Last Exam scores 27.3, ahead of Opus's 25.7. ZeroBench Pass@5 lands at 35.0 against Opus's 34.0, and Chartography at 64.3 against 65.0. On text-only agent tasks the gap is narrower: Terminal Bench 2.1 at 83.9 versus Opus's 85.0, DeepSWE at 59.3 versus Opus's 58.0, and NL2Repo at 57.7 against Opus's 69.7.

Weights ship with `vllm serve` and SGLang launch commands baked into the README, a minimal PyTorch inference script, and quantizations flagged for llama.cpp, Ollama and LM Studio. No paper or blog post accompanied the drop.

It arrives two days after Tencent open-sourced Hy4-preview, continuing the pace on the China AI beat we track.