Model comparison
Claude 2.1 vs DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 25.2 on the Noometry Index.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. Claude 2.1 scores higher in 0 categories and DeepSeek-V3.1-Terminus in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 38.5 to 10.2.
- The biggest single-benchmark swing is DTBench: 51% for Claude 2.1 and 81.3% for DeepSeek-V3.1-Terminus.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| Claude 2.1 | DeepSeek-V3.1-Terminus | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 25.2 | 43.1 |
| Released | 2023-11-21 | 2025-09-22 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 147K |
| Input $ / M tokens | — | $0.27 |
| Output $ / M tokens | — | $1 |
| Results tracked | 7 | 16 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
Claude 2.1: 26.2 (#327), DeepSeek-V3.1-Terminus: 42.0 (#113)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| SciCode | — | 40.6% |
| WeirdML | 7.1% | — |
| LMArena Coding | — | 1426 |
| ALE-Bench | — | 745.17 |
Reasoning DeepSeek-V3.1-Terminus leads
Claude 2.1: 21.4 (#221), DeepSeek-V3.1-Terminus: 26.4 (#133)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| DTBench | 51% | 81.3% |
| Kagi LLM Benchmark | — | 57.4% |
| CritPt | — | 1.7% |
| LMArena Hard Prompts | — | 1426 |
| LMCA | — | 28.6% |
| Epoch Capabilities Index | 119.27 | — |
| ForecastBench | 54.2 | — |
Math DeepSeek-V3.1-Terminus leads
Claude 2.1: 10.2 (#315), DeepSeek-V3.1-Terminus: 38.5 (#137)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | — | 1402 |
Knowledge Not comparable
Claude 2.1: 15.4 (#292), DeepSeek-V3.1-Terminus: —
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| GPQA Diamond | 33% | — |
| MMLU | 73.5% | — |
Multilingual Not comparable
Claude 2.1: —, DeepSeek-V3.1-Terminus: 52.1 (#92)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Non-English | — | 1407 |
| LMArena Russian | — | 1436 |
Instruction Following Not comparable
Claude 2.1: —, DeepSeek-V3.1-Terminus: 74.0 (#106)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Instruction Following | — | 1404 |
Long Context Not comparable
Claude 2.1: —, DeepSeek-V3.1-Terminus: 43.4 (#97)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Longer Query | — | 1421 |
Writing & Preference Not comparable
Claude 2.1: —, DeepSeek-V3.1-Terminus: 61.0 (#92)
| Benchmark | Claude 2.1 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Text | — | 1419 |
| LMArena Creative Writing | — | 1403 |
| LMArena Multi-Turn | — | 1411 |
Frequently asked questions
Is Claude 2.1 better than DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 25.2 on the Noometry Index.
Is Claude 2.1 or DeepSeek-V3.1-Terminus better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 26.2 in the Noometry coding category.
How many benchmarks do Claude 2.1 and DeepSeek-V3.1-Terminus share?
1 benchmark has published results for both models. Claude 2.1 has 7 scored results on Noometry and DeepSeek-V3.1-Terminus has 16.