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Quick Answer

DeepSeek V4 Open Weights: MIT License (August 2026)

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The Short Answer

In August 2026, DeepSeek released the weights for its V4/0731 model under an MIT license — a 284B-parameter mixture-of-experts model with just 13B active parameters. It’s one of the most permissive frontier open-weight releases of the year: commercial use, self-hosting, and redistribution all allowed.

Key Facts

DeepSeek V4/0731
LicenseMIT (fully permissive)
Total parameters~284B (mixture-of-experts)
Active parameters~13B per token
API price (V4 Pro, off-peak)$0.435 / $0.87 per MTok
API price (V4 Flash, off-peak)$0.14 / $0.28 per MTok
Cache-hit (V4 Pro)~$0.043

What the MIT License Changes

Many “open” models ship under custom licenses that restrict commercial use above a user threshold or forbid training competing models. MIT does none of that — it’s a permissive license allowing commercial deployment, modification, and redistribution with essentially just an attribution requirement. For teams that want a frontier-class model they can self-host without legal friction, this is the headline.

The 284B / 13B Architecture

V4/0731 is a mixture-of-experts (MoE) design: 284B total parameters but only ~13B active per token. That means inference cost and speed track the 13B active count, not the full 284B — so it runs far cheaper than a dense 284B model while retaining the capacity to match much larger models on many tasks. It’s the same efficiency pattern that made earlier DeepSeek releases cost-competitive.

API vs Self-Host

  • API (managed): V4 Pro ~$0.435/$0.87 per MTok off-peak (2× during peak hours 1-4 and 6-10 UTC); V4 Flash $0.14/$0.28. Note the deepseek-chat / -reasoner names were retired July 24, 2026.
  • Self-host (MIT weights): you pay only your own GPU/compute — attractive for data-sovereignty needs or very high volume where API markup dominates.

Who Should Care

  • Self-hosters wanting a permissively-licensed frontier model.
  • High-volume API users comparing DeepSeek’s cheap off-peak rates against Western frontier pricing.
  • Enterprises with data-residency requirements that rule out managed APIs.

The Reality Check

An MIT-licensed 284B MoE is a big deal for the open ecosystem — but “open weights” isn’t “cheap to run.” You still need multi-GPU hardware to serve 284B params, even with 13B active. For most teams the off-peak API is the practical path; self-hosting pays off only at serious scale or under strict data-sovereignty rules.

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