Term
DeepSeek V4-Pro
DeepSeek V4-Pro (2026) is DeepSeeks open-weight flagship — a 1.6-trillion-parameter MoE with about 49B active parameters per token, a 1M-token context and an MIT license.
DeepSeek V4-Pro — explained in more detail
DeepSeek V4-Pro is the flagship of the V4 generation from the Chinese lab DeepSeek, released in 2026 under the MIT license. The defining trait: it is an open-weight model — the trained weights can be downloaded and run locally, unlike pure API models such as GPT or Claude whose weights stay closed. Open weight is not the same as fully open source, though: training data and the complete training code usually remain undisclosed.
Architecturally, V4-Pro is a Mixture-of-Experts (MoE) with roughly 1.6 trillion total parameters, of which only about 49 billion are active per token. This sparse design is the lever that keeps very large models affordable: instead of computing the whole network for every request, a router activates only a small subset of experts. The context window is around 1 million tokens. In benchmarks V4-Pro reaches about 80 percent on SWE-bench Verified (real bug-fix tasks), roughly 90 on MMLU and above 90 on maths tests such as MATH-500 — figures that place it at the top of open models.
DeepSeek ships V4 as a two-tier release: V4-Pro as the flagship and V4-Flash as a lighter variant with around 284 billion total parameters (about 13B active) for faster, cheaper inference. Both share the 1M context window and hybrid reasoning modes.
Example / Practical context
The practical appeal of V4-Pro lies in the combination of frontier performance and an open license. A company with data-protection requirements can run the model on its own or rented GPU hardware without sending data to an external API provider — provided the necessary compute is available (a 1.6T MoE needs substantial VRAM). Typical uses are long-running agentic workflows, code generation across large repositories, and reasoning-heavy tasks where the 1M context holds all the relevant material.
Distinction from related terms
Within the V4 line, V4-Pro sits above the smaller, cheaper V4-Flash. It differs fundamentally from the API-only models (GPT, Claude, Gemini) through its open weights and MIT license — the central positioning difference. Among open frontier models it competes with Qwen (Alibaba), GLM, Kimi (Moonshot) and MiniMax; DeepSeek positions itself on the combination of large MoE capacity, long context and an aggressive price-performance ratio. V4-Pro should not be confused with the separate base entry DeepSeek V4 (the generation as a whole) — V4-Pro specifically denotes the flagship tier.