DeepSeek V3.1 ships 671B/37B hybrid reasoning weights under MIT at $0.56/$1.68 per million tokens
DeepSeek released DeepSeek-V3.1, one checkpoint that switches between thinking and non-thinking modes through the chat template: 671B total parameters, 37B activated per token, a 128K context window, and MIT-licensed weights on Hugging Face. The model card reports SWE-bench Verified 66.0 and Terminal-bench 31.3 in agent mode, BrowseComp 30.0 against 8.9 for the May R1 refresh, and AIME 2025 88.4 in thinking mode — tool-use and reasoning scores in the range closed frontier models occupied earlier in 2025. It is trained in the UE8M0 FP8 scale format for microscaling hardware, a deliberate hedge toward non-Nvidia inference.
List pricing at launch was $0.07 per million cached input tokens, $0.56 per million input tokens and $1.68 per million output tokens on the chat endpoint, with a 50% off-peak discount on top. DeepSeek's own release note flagged that new pricing takes effect, and off-peak discounts end, on September 5, 2025.

WHY IT MATTERS
A 671B/37B MoE in FP8 is an eight-GPU-class serving decision, not a laptop download, so the real choice is self-host with real capex or rent near-frontier agent behavior at a low per-token rate. Either way, keep the rate card in config rather than code: this release shipped with a scheduled price change three weeks out, which is exactly the versioning problem a hardcoded cost model fails.





