DeepSeek model product
1 is a hybrid large language model with thinking and non-thinking modes, 671B total parameters, and 37B activated parameters.
Updated Sep 8, 2026. Default version: DeepSeek-V3.1
This profile uses the model's current scored version. Arena ratings and prices are shown separately.
Benchmark scores for DeepSeek-V3.1.
Benchmark | Score | Rank | Participants | Percentile | Evidence | Evaluated |
|---|
| BenchmarkSimpleQA | Score93.40% | Rank03 | Participants47 | Percentile95.65% | EvidenceC | Evaluated |
| BenchmarkAider-Polyglot | Score68.40% | Rank08 | Participants22 | Percentile66.67% | EvidenceC | Evaluated |
| BenchmarkBrowseComp-zh | Score49.20% | Rank10 | Participants13 | Percentile25.00% | EvidenceC | Evaluated |
| BenchmarkCodeForces | Score69.70% | Rank13 | Participants17 | Percentile25.00% | EvidenceC | Evaluated |
| BenchmarkTerminal-Bench | Score31.30% | Rank18 | Participants25 | Percentile29.17% | EvidenceC | Evaluated |
| BenchmarkMMLU-Redux | Score91.80% | Rank21 | Participants48 | Percentile57.45% | EvidenceC | Evaluated |
| BenchmarkHMMT 2025 | Score33.50% | Rank32 | Participants33 | Percentile3.13% | EvidenceC | Evaluated |
| BenchmarkMMLU-Pro | Score83.70% | Rank33 | Participants138 | Percentile76.64% | EvidenceC | Evaluated |
| BenchmarkSWE-bench Multilingual | Score54.50% | Rank35 | Participants43 | Percentile19.05% | EvidenceC | Evaluated |
| BenchmarkLiveCodeBench | Score56.40% | Rank38 | Participants75 | Percentile50.00% | EvidenceC | Evaluated |
| BenchmarkAIME 2024 | Score66.30% | Rank43 | Participants53 | Percentile19.23% | EvidenceC | Evaluated |
| BenchmarkBrowseComp | Score30.00% | Rank60 | Participants63 | Percentile4.84% | EvidenceC | Evaluated |
| BenchmarkSWE-Bench Verified | Score66.00% | Rank77 | Participants113 | Percentile32.14% | EvidenceC | Evaluated |
| BenchmarkHumanity's Last Exam | Score15.90% | Rank78 | Participants103 | Percentile24.51% | EvidenceC | Evaluated |
| BenchmarkLM Arena Text | Score1,420.30 rating | Rank79 | Participants210 | Percentile62.68% | EvidenceA | Evaluated |
| BenchmarkLM Arena Text Style Control | Score1,417.53 rating | Rank91 | Participants210 | Percentile56.94% | EvidenceA | Evaluated |
| BenchmarkAIME 2025 | Score49.80% | Rank105 | Participants119 | Percentile11.86% | EvidenceC | Evaluated |
| BenchmarkGPQA | Score74.90% | Rank119 | Participants247 | Percentile52.03% | EvidenceC | Evaluated |
Preference and agent-evaluation results for the default version.
Arena | Category | Rank | Rating / score | Votes | Observations | Result date |
|---|
| Arenatext | Categoryindustry medicine and healthcare | Rank29 | Rating / score1,466.91 | Votes227 | ObservationsN/A | Result date |
| Arenatext | Categoryindustry legal and government | Rank35 | Rating / score1,459.24 | Votes257 | ObservationsN/A | Result date |
| Arenatext style control | Categoryindustry legal and government | Rank48 | Rating / score1,462.76 | Votes257 | ObservationsN/A | Result date |
| Arenatext | Categoryrussian | Rank51 | Rating / score1,434.67 | Votes284 | ObservationsN/A | Result date |
| Arenatext | Categoryindustry life and physical and social science | Rank54 | Rating / score1,452.24 | Votes572 | ObservationsN/A | Result date |
| Arenatext | Categorychinese | Rank57 | Rating / score1,469.97 | Votes1,150 | ObservationsN/A | Result date |
| Arenatext | Categorypolish | Rank57 | Rating / score1,429.27 | Votes208 | ObservationsN/A | Result date |
| Arenatext | Categoryfrench | Rank60 | Rating / score1,448.22 | Votes286 | ObservationsN/A | Result date |
| Arenatext | Categoryindustry writing and literature and language | Rank61 | Rating / score1,411.95 | Votes754 | ObservationsN/A | Result date |
| Arenatext style control | Categoryindustry medicine and healthcare | Rank61 | Rating / score1,463.91 | Votes227 | ObservationsN/A | Result date |
| Arenatext | Categoryindustry mathematical | Rank63 | Rating / score1,439.06 | Votes564 | ObservationsN/A | Result date |
| Arenatext style control | Categoryindustry mathematical | Rank63 | Rating / score1,444.43 | Votes564 | ObservationsN/A | Result date |
| Arenatext style control | Categorylonger query | Rank64 | Rating / score1,448.00 | Votes672 | ObservationsN/A | Result date |
| Arenatext | Categorycreative writing | Rank65 | Rating / score1,402.16 | Votes450 | ObservationsN/A | Result date |
| Arenatext style control | Categorycreative writing | Rank69 | Rating / score1,403.92 | Votes450 | ObservationsN/A | Result date |
| Arenatext style control | Categoryindustry writing and literature and language | Rank69 | Rating / score1,411.84 | Votes754 | ObservationsN/A | Result date |
| Arenatext style control | Categoryjapanese | Rank69 | Rating / score1,380.55 | Votes329 | ObservationsN/A | Result date |
| Arenatext | Categoryspanish | Rank70 | Rating / score1,428.47 | Votes409 | ObservationsN/A | Result date |
| Arenatext style control | Categoryindustry life and physical and social science | Rank70 | Rating / score1,452.93 | Votes572 | ObservationsN/A | Result date |
| Arenatext style control | Categoryrussian | Rank71 | Rating / score1,429.20 | Votes284 | ObservationsN/A | Result date |
| Arenatext | Categorylonger query | Rank72 | Rating / score1,424.97 | Votes672 | ObservationsN/A | Result date |
| Arenatext style control | Categorychinese | Rank72 | Rating / score1,471.73 | Votes1,150 | ObservationsN/A | Result date |
| Arenatext style control | Categorypolish | Rank72 | Rating / score1,419.64 | Votes208 | ObservationsN/A | Result date |
| Arenatext style control | Categoryspanish | Rank72 | Rating / score1,421.78 | Votes409 | ObservationsN/A | Result date |
| Arenatext | Categorygerman | Rank73 | Rating / score1,410.78 | Votes397 | ObservationsN/A | Result date |
| Arenatext style control | Categoryinstruction following | Rank74 | Rating / score1,421.36 | Votes853 | ObservationsN/A | Result date |
| Arenatext | Categoryindustry business and management and financial operations | Rank75 | Rating / score1,417.45 | Votes689 | ObservationsN/A | Result date |
| Arenatext | Categoryjapanese | Rank75 | Rating / score1,374.20 | Votes329 | ObservationsN/A | Result date |
| Arenatext style control | Categoryfrench | Rank75 | Rating / score1,447.12 | Votes286 | ObservationsN/A | Result date |
| Arenatext | Categoryinstruction following | Rank76 | Rating / score1,407.32 | Votes853 | ObservationsN/A | Result date |
Official vendor API pricing appears first, followed by individual provider offers.
Provider | Provider model ID | Region | Input / 1M | Output / 1M | Context | Updated |
|---|
| ProviderTokenGo | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.19 | Output / 1M$0.71 | Context131.1K | Updated |
| ProviderNanoGPT | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.20 | Output / 1M$0.70 | Context128K | Updated |
| Providersubmodel | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.20 | Output / 1M$0.80 | Context75K | Updated |
| ProviderDeep Infra | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.25 | Output / 1M$0.95 | Context163.8K | Updated |
| ProviderOpenRouter | Provider model IDdeepseek/deepseek-chat-v3.1 | Regionglobal | Input / 1M$0.25 | Output / 1M$0.95 | Context163.8K | Updated |
| ProviderVercel AI Gateway | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.25 | Output / 1M$0.95 | Context163.8K | Updated |
| ProviderMeganova | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.27 | Output / 1M$1 | Context164K | Updated |
| ProviderHugging Face | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.27 | Output / 1M$1 | Context131.1K | Updated |
| ProviderJiekou.AI | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.27 | Output / 1M$1 | Context163.8K | Updated |
| ProviderNovitaAI | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.27 | Output / 1M$1 | Context131.1K | Updated |
| ProviderMerge Gateway | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.50 | Output / 1M$1.5 | Context164K | Updated |
| ProviderBaseten | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.50 | Output / 1M$1.5 | Context164K | Updated |
| ProviderWeights & Biases | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.55 | Output / 1M$1.65 | Context161K | Updated |
| ProviderAbacus | Provider model IDdeepseek/deepseek-v3.1 | Regionglobal | Input / 1M$0.55 | Output / 1M$1.66 | Context128K | Updated |
| ProviderPioneer | Provider model IDdeepseek-ai/DeepSeek-V3.1 | Regionglobal | Input / 1M$0.56 | Output / 1M$1.68 | Context163.8K | Updated |
| ProviderAlibaba (China) | Provider model IDdeepseek-v3-1 | Regionglobal | Input / 1M$0.574 | Output / 1M$1.72 | Context131.1K | Updated |
| ProviderAmazon Bedrock | Provider model IDdeepseek.v3-v1:0 | Regionglobal | Input / 1M$0.58 | Output / 1M$1.68 | Context163.8K | Updated |
| ProviderVertex | Provider model IDdeepseek-ai/deepseek-v3.1-maas | Regionglobal | Input / 1M$0.60 | Output / 1M$1.7 | Context163.8K | Updated |
| ProviderTogether AI | Provider model IDdeepseek-ai/DeepSeek-V3-1 | Regionglobal | Input / 1M$0.60 | Output / 1M$1.7 | Context131.1K | Updated |
Provider-specific output speed and catalog latency for DeepSeek-V3.1. Runtime does not affect the capability score.
No provider-specific speed or latency record is linked to the default version yet.
Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.
Technical details for the model's default version.
Available versions of this model. The score column identifies the version used in the overall ranking.
Version | Released | LLMBoard | Parameters | Context | Max output | Open weights | License |
|---|
| VersionDeepSeek-V3.1 | Released | LLMBoard39.05 | Parameters671B | Context163.8K | Max output163.8K | Open weightsYes | LicenseMIT |
Recommendations prioritize the same model type and family, then the closest LLMBoard score.
Key information about DeepSeek-V3.1 and its available data.
1-Base that supports thinking and non-thinking modes through different chat templates. It uses a two-phase long context extension, supports up to 128K context, and uses the UE8M0 FP8 scale data format for model weights and activations.
Data as of 2026-09-08.
Common questions about DeepSeek-V3.1.
DeepSeek-V3.1's default version was released on Jan 10, 2025.
No official standard PAYG price is currently available for DeepSeek-V3.1. The lowest tracked third-party offer starts at $0.19 input and $0.71 output via TokenGo.
DeepSeek-V3.1 was created by DeepSeek.
The default version has a 163.8K token context window.
Yes. The default version is marked as open weight under MIT.
20 provider offerings are linked to the default version.
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.