Model comparison
Claude 3.7 Sonnet vs DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 39.4 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeekSummary
- They share 10 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 2 categories and DeepSeek-V3.1-Terminus in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where DeepSeek-V3.1-Terminus leads 52.3 to 44.3.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 39.4 | 42.6 |
| Released | 2025-02-24 | 2025-09-22 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $1 |
| Results tracked | 58 | 16 |
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Category by category
Coding Too close to call
Claude 3.7 Sonnet: 41.1 (#120), DeepSeek-V3.1-Terminus: 41.5 (#114)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Coding | 1361 | 1426 |
| SWE-bench Verified | 61% | — |
| SWE-bench Verified (bash only) | 52.8% | — |
| Aider Polyglot | 64.9% | — |
| SciCode | — | 40.6% |
| GSO | 3.8% | — |
| LiveBench Coding | 74.5% | — |
| CadEval | 54% | — |
| ALE-Bench | — | 745.17 |
Agentic & Tool Use Not comparable
Claude 3.7 Sonnet: 33.9 (#46), DeepSeek-V3.1-Terminus: —
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| TheAgentCompany | 30.9% | — |
| Cybench | 20% | — |
| DeepResearch Bench | 43.6% | — |
| OSWorld | 35.8% | — |
| METR Time Horizons | 60% | — |
Reasoning DeepSeek-V3.1-Terminus leads
Claude 3.7 Sonnet: 18.7 (#252), DeepSeek-V3.1-Terminus: 25.7 (#126)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Hard Prompts | 1333 | 1427 |
| ARC-AGI-2 | 0.9% | — |
| SimpleBench | 46.4% | — |
| Kagi LLM Benchmark | — | 57.4% |
| ARC-AGI-1 | 28.6% | — |
| CritPt | — | 1.7% |
| EnigmaEval | 4.2% | — |
| LiveBench Reasoning | 87.8% | — |
| DTBench | — | 81.3% |
| LiveBench Data Analysis | 74% | — |
| LMCA | — | 28.6% |
| Epoch Capabilities Index | 141.16 | — |
| ForecastBench | 61.8 | — |
| LiveBench | 76.1% | — |
Math Too close to call
Claude 3.7 Sonnet: 35.7 (#137), DeepSeek-V3.1-Terminus: 35.7 (#138)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Math | 1336 | 1402 |
| OTIS Mock AIME 2024-2025 | 57.8% | — |
| Omni-MATH | 33% | — |
| LiveBench Math | 79% | — |
| MATH Level 5 | 91.2% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
Knowledge Not comparable
Claude 3.7 Sonnet: 39.7 (#117), DeepSeek-V3.1-Terminus: —
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| GPQA Diamond | 79.7% | — |
| Humanity's Last Exam | 8% | — |
| MMLU-Pro | 78.4% | — |
| Confabulations | 14.7% | — |
| GPQA (HELM) | 60.8% | — |
| LMArena Expert | 1321 | — |
Multimodal Not comparable
Claude 3.7 Sonnet: 33.1 (#90), DeepSeek-V3.1-Terminus: —
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Vision | 1169 | — |
| GeoBench | 68% | — |
| VPCT | 39% | — |
| SpatialViz-Bench | 33.9% | — |
Multilingual DeepSeek-V3.1-Terminus leads
Claude 3.7 Sonnet: 44.3 (#174), DeepSeek-V3.1-Terminus: 52.3 (#87)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Non-English | 1296 | 1407 |
| LMArena Russian | 1311 | 1434 |
| LMArena Chinese | 1299 | — |
| LMArena French | 1302 | — |
| LMArena German | 1301 | — |
| LMArena Japanese | 1268 | — |
| LMArena Korean | 1249 | — |
| LMArena Spanish | 1299 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
Claude 3.7 Sonnet: 73.1 (#120), DeepSeek-V3.1-Terminus: 74.4 (#96)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Instruction Following | 1352 | 1406 |
| LiveBench Instruction Following | 81.3% | — |
| IFEval | 83.4% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.2 (#10), DeepSeek-V3.1-Terminus: 43.5 (#88)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Longer Query | 1373 | 1426 |
| Fiction.LiveBench | 83.3% | — |
Writing & Preference DeepSeek-V3.1-Terminus leads
Claude 3.7 Sonnet: 54.6 (#145), DeepSeek-V3.1-Terminus: 61.3 (#87)
| Benchmark | Claude 3.7 Sonnet | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Text | 1314 | 1420 |
| LMArena Creative Writing | 1332 | 1404 |
| LMArena Multi-Turn | 1339 | 1411 |
| Short-Story Creative Writing | 81.1% | — |
| EQ-Bench Creative Writing | 1412 | — |
| WildBench | 81.4% | — |
| LiveBench Language | 59.9% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 39.4 on the Noometry Index.
Is Claude 3.7 Sonnet or DeepSeek-V3.1-Terminus better for coding?
They score almost the same on coding (41.1 vs 41.5); test both on your own repository before choosing.
How many benchmarks do Claude 3.7 Sonnet and DeepSeek-V3.1-Terminus share?
10 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and DeepSeek-V3.1-Terminus has 16.