DeepSeek open-sources first V4 vision model under MIT license

DeepSeek has extended its V4 family into multimodality with V4-Flash-Vision-Exp, its first vision model, released with open weights on August 31. The model is a 305-billion-parameter sparse Mixture-of-Experts architecture, freely downloadable under a permissive MIT license — analysts describe it as the first model in its class that a developer can actually obtain and run, contrasting with the closed, gated releases dominating U.S. frontier labs.

The MIT licensing is the strategic differentiator. As Meta abandons open-weight Llama for closed Muse Spark and OpenAI/Anthropic gate cyber-capable models behind refusal-rate controls, DeepSeek is doubling down on genuinely open distribution — a move that reignites the open- vs closed-weights debate and appeals directly to the r/LocalLLaMA community and cost-sensitive builders. The sparse MoE design keeps active-parameter inference costs lower than the 305B total would suggest.

The release is part of an accelerating Chinese model surge: analysts expect an upgraded DeepSeek V5 in the second half of 2026, and Aurora Mobile's Modellix.ai launched a beta plugin for the DeepSeek Harness. Separately, B.AI announced its free trial for DeepSeek V4 Flash and V4 Flash Vision Exp ends September 3, moving to discounted billing at 50% (peak) and 25% (off-peak) of official rates. Skeptics caution that DeepSeek's benchmark claims 'need independent proof,' echoing broader concerns about vendor-cited scores. Still, an MIT-licensed frontier-adjacent vision MoE is a genuine gift to the open ecosystem at a moment when open weights are increasingly scarce among leading labs.