Model profile
DeepSeek-R1
Evidence coverage
11 of 321 tracked benchmarks are published. 0 are verified and 11 provisional. 5 of 8 categories are measured.
- Published / tracked
- 11 / 321
- Verified
- 0
- Provisional
- 11
- Categories with evidence
- 5 / 8
Evidence by category
- Agentic1 benchmarkReported
- Coding1 benchmarkReported
- Reasoning2 benchmarksReported
- Knowledge6 benchmarksReported
- Math0 benchmarksNot measured
- Multilingual0 benchmarksNot measured
- Multimodal0 benchmarksNot measured
- Inst. Following1 benchmarkReported
DeepSeek-R1 ranks #103 out of 200 models on the public leaderboard with an overall score of 51.67/100. It also ranks #56 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
DeepSeek-R1 is a open weight model with a 128K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 11 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 51.25–52.15
- Qwen2.5-72BAlibabaCompare#10152.15Qwen2.5-72B is #101 with a score of 52.15.
- Llama 3.1 405BMetaCompare#10251.71Llama 3.1 405B is #102 with a score of 51.71.
- DeepSeek-R1Current modelDeepSeek#10351.67DeepSeek-R1 is #103 with a score of 51.67.
- Qwen3.6-35B-A3BAlibabaCompare#10451.47Qwen3.6-35B-A3B is #104 with a score of 51.47.
- Mercury 2InceptionCompare#10551.28Mercury 2 is #105 with a score of 51.28.
- GLM-4.7-FlashZ.AICompare#10651.25GLM-4.7-Flash is #106 with a score of 51.25.
- Grok 4.1 FastxAICompare#10751.25Grok 4.1 Fast is #107 with a score of 51.25.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank Not rankedWeight 22%1 benchmarkReported | 44.6 | Not ranked | Not available | 22% | 1 benchmark | Reported |
| CodingRank Not rankedWeight 20%1 benchmarkReported | 27.5 | Not ranked | Not available | 20% | 1 benchmark | Reported |
| ReasoningRank Not rankedWeight 17%2 benchmarksReported | 40.1 | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank Not rankedWeight 12%6 benchmarksReported | 42.7 | Not ranked | Not available | 12% | 6 benchmarks | Reported |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 83.3 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1398 | ±4.9 | 18,524 |
| Coding | 1445 | ±11.8 | 2,317 |
| Math | 1412 | ±14.0 | 1,606 |
| Instruction Following | 1397 | ±7.5 | 6,426 |
| Creative Writing | 1374 | ±10.4 | 3,289 |
| Multi-turn | 1410 | ±11.9 | 2,418 |
| Hard Prompts | 1419 | ±9.0 | 4,116 |
| Hard Prompts (English) | 1433 | ±11.2 | 2,656 |
| Longer Query | 1399 | ±12.0 | 2,303 |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic1 benchmark
τ²-Bench Tool-Agent-User Evaluation
Coding1 benchmark
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge6 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does DeepSeek-R1 perform overall in AI benchmarks?
DeepSeek-R1 has 11 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is DeepSeek-R1 good for knowledge and understanding?
DeepSeek-R1 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek-R1 good for coding and programming?
DeepSeek-R1 has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek-R1 good for reasoning and logic?
DeepSeek-R1 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek-R1 good for agentic tool use and computer tasks?
DeepSeek-R1 has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek-R1 good for instruction following?
DeepSeek-R1 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek-R1 open source?
Yes, DeepSeek-R1 is an open weight model created by DeepSeek, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does DeepSeek-R1 have full benchmark coverage on BenchLM?
Not yet. DeepSeek-R1 currently has 11 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of DeepSeek-R1?
DeepSeek-R1 has a published context window of 128K, which determines how much text it can process in a single interaction.
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