DeepSeek V4

DeepSeek·Mar 2026reasoningopen weights · MIT

DeepSeek V4 did to 2026 what its R1 did to 2025: proved that open-weights models can sit at the frontier. It scores around 81% on SWE-bench Verified — within a few points of Claude Opus 4.8 — with a 1M-token context, hybrid reasoning modes, and API pricing an order of magnitude below US flagships. Under MIT license, it can be self-hosted, fine-tuned and embedded commercially without restriction, making it the default open frontier model for cost-sensitive and sovereignty-sensitive deployments alike.

Benchmark results

Where it shines

  • Frontier-class coding within a few points of closed flagships
  • 10–50x cheaper than comparable proprietary APIs
  • MIT license — unrestricted commercial use and fine-tuning
  • 1M-token context window

Alternatives to DeepSeek V4

Frequently asked questions

How much does the DeepSeek V4 API cost?
DeepSeek V4 costs $0.3 per million input tokens and $0.5 per million output tokens, with cached input at $0.03 per million. A workload of 10M input and 1.5M output tokens per month costs about $3.75.
What is the context window of DeepSeek V4?
DeepSeek V4 supports a context window of 1,000,000 tokens (1M), with up to 64K output tokens per response.
Is DeepSeek V4 open source?
Yes — DeepSeek V4 is an open-weights model released under the MIT license, so it can be downloaded and self-hosted.
What are the best alternatives to DeepSeek V4?
The closest alternatives by overall capability are Qwen3-Max, GPT-5.5, Gemini 3 Pro, Gemini 2.5 Pro. See the comparison pages for detailed head-to-head breakdowns.