MDL-9623EST.2026 · IDX.208
Language modelIn production

DeepSeek-V4-Pro

DeepSeek · China · 2026

DeepSeek's flagship: a 1.6-trillion-parameter MoE with open weights under MIT, matching closed frontier models on coding at a fraction of their price.

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DeepSeek-V4-Pro is the flagship of DeepSeek's fourth-generation line and the larger of the two V4 variants the company shipped. It is a sparse mixture-of-experts model with 1.6 trillion total parameters, of which roughly 49 billion are activated per token, and it shares the one-million-token context window of its smaller sibling V4-Flash. Like the rest of the line it is text-only — no vision, audio or video input. The model was first published as a preview on 24 April 2026 and reached general availability on 19 July 2026. The weights did not change between the two milestones; what changed was the commercial packaging. DeepSeek introduced peak-time pricing for the first time, doubling rates during Beijing business hours, and retired the legacy deepseek-chat and deepseek-reasoner API endpoints on 24 July 2026, forcing callers onto explicit model IDs. On DeepSeek's published GA figures V4-Pro scores 80.6% on SWE-bench Verified — the strongest open-weights result on that benchmark — alongside a Codeforces rating of 3,206, 57.9% on SimpleQA Verified and 37.7% on Humanity's Last Exam. Independent measurement is less flattering to the trend line: Artificial Analysis placed V4-Pro at 44 points on its Intelligence Index at GA, down from 52 at preview, not because the model regressed but because the frontier moved during the three-month gap. The economics are the real argument. Off-peak API pricing is 0.435 US dollars per million input tokens and 0.87 per million output, with cached input at roughly a hundredth of that — an order of magnitude below Western frontier models of comparable coding ability. The weights are on Hugging Face under the MIT licence, so the model can also be self-hosted outright. DeepSeek-V4-Flash and the earlier DeepSeek-R1 remain available and have their own profiles in this catalogue.

#MoE#open weights#MIT license#long context#agentic coding#frontier#China
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