specs at a glance
| Leaderboard rank | #5 of 10 |
|---|---|
| SWE-bench Verified | 80.6% |
| SWE-bench Pro | 55.4% |
| Terminal-Bench | 67.9% (TB2.0) |
| Input price / 1M | $0.435 |
| Output price / 1M | $0.87 |
| Context window | 1M |
| Open weights | Yes |
| Access | Open weights (MIT) · API · self-host |
| Maker | DeepSeek |
how good is DeepSeek V4 Pro at coding?
DeepSeek V4 Pro sits at #5 of 10 ranked models, posting 80.6% on SWE-bench Verified — 14.4 points behind #1 Claude Fable 5. On the harder SWE-bench Pro it scores 55.4%. Terminal-Bench (agentic terminal work): 67.9% (TB2.0).
Score provenance: Independent tracker (llm-stats, June 2026); tied with Gemini 3.1 Pro on Verified, ahead on Pro.
what does DeepSeek V4 Pro cost?
$0.435 per 1M input tokens and $0.87 per 1M output — the cheapest model we track. Coding workloads are output-heavy, so weight the output rate when budgeting. Run your own volume through the AI API cost calculator for a monthly estimate.
where can you use it?
Available via Open weights (MIT) · API · self-host. Because it ships open weights, you can also self-host it on your own hardware or any inference provider — with the version pinned so the model can't change under you.
head-to-head
- DeepSeekDeepSeek V4 — specs & benchmarks
Ranked on our AI Coding Leaderboard — scores confirmed against primary sources only, updated 2026-07-04.