Model comparison
Claude Opus 4.1 vs DeepSeek-R1
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 41.0 on the Noometry Index.
Last verified . 30 shared benchmarks.
DeepSeekSummary
- They share 30 benchmarks with published results for both. Claude Opus 4.1 scores higher in 4 categories and DeepSeek-R1 in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-R1 leads 43.8 to 22.3.
- The biggest single-benchmark swing is SimpleBench: 60% for Claude Opus 4.1 and 40.8% for DeepSeek-R1.
- DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $15 / $75 for Claude Opus 4.1.
- Claude Opus 4.1 accepts more context: 200K tokens versus 164K.
Side by side
| Claude Opus 4.1 | DeepSeek-R1 | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 41.0 | 42.3 |
| Released | 2025-08-05 | 2025-01-20 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 164K |
| Max output | 32K | 64K |
| Input $ / M tokens | $15 | $0.50 |
| Output $ / M tokens | $75 | $2.15 |
| Results tracked | 48 | 52 |
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Category by category
Coding DeepSeek-R1 leads
Claude Opus 4.1: 44.4 (#73), DeepSeek-R1: 46.3 (#68)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| WeirdML | 45.9% | 41.6% |
| LMArena Coding | 1479 | 1427 |
| ALE-Bench | 674.77 | 804.12 |
| AlgoTune | 1.34 | 1.7 |
| SWE-bench Verified | 73.3% | — |
| Aider Polyglot | — | 71.4% |
| LMArena WebDev | 1390 | — |
| SciCode | — | 35.7% |
| LiveBench Coding | — | 66.7% |
Agentic & Tool Use Claude Opus 4.1 leads
Claude Opus 4.1: 35.0 (#41), DeepSeek-R1: 30.7 (#75)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | 48.3% | 35.1% |
| METR Time Horizons | 66.8% | 53.8% |
| Terminal-Bench | 38% | — |
| GDPval | 43.6% | — |
| Cybench | 42% | — |
| BALROG | — | 34.9% |
| LMArena Search | 1148 | — |
Reasoning Claude Opus 4.1 leads
Claude Opus 4.1: 32.2 (#76), DeepSeek-R1: 18.6 (#278)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| SimpleBench | 60% | 40.8% |
| LMArena Hard Prompts | 1443 | 1416 |
| Epoch Capabilities Index | 144.12 | 141.29 |
| ForecastBench | 62 | 60 |
| ARC-AGI-2 | — | 1.3% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 21.2% |
| CritPt | — | 1.1% |
| Chess Puzzles | 7% | — |
| EnigmaEval | 7.2% | — |
| EBR-Bench | 7.9% | — |
| LiveBench Reasoning | — | 83.2% |
| Mystery Game Puzzles | 21% | — |
| DTBench | 80% | — |
| LiveBench Data Analysis | — | 69.8% |
| LMCA | 37.1% | — |
| LiveBench | — | 71.6% |
Math DeepSeek-R1 leads
Claude Opus 4.1: 22.3 (#277), DeepSeek-R1: 43.8 (#79)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 68.9% | 66.4% |
| LMArena Math | 1431 | 1400 |
| FrontierMath (Tiers 1-3) | 12.6% | — |
| FrontierMath Tier 4 | 2.4% | — |
| Omni-MATH | — | 42.4% |
| LiveBench Math | — | 80.7% |
| MATH Level 5 | — | 96.6% |
| FrontierMath (Feb 2025 set) | 7.2% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge DeepSeek-R1 leads
Claude Opus 4.1: 42.0 (#101), DeepSeek-R1: 44.5 (#87)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| GPQA Diamond | 77.3% | 76.3% |
| Confabulations | 17.1% | 12.7% |
| Vectara Hallucination Rate | 11.8% | 11.3% |
| LMArena Expert | 1439 | 1394 |
| Humanity's Last Exam | 11.5% | — |
| MMLU-Pro | — | 79.3% |
| GPQA (HELM) | — | 66.6% |
Multimodal Not comparable
Claude Opus 4.1: 26.8 (#119), DeepSeek-R1: —
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| VPCT | 35% | — |
Multilingual Too close to call
Claude Opus 4.1: 52.0 (#95), DeepSeek-R1: 52.4 (#85)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1405 | 1412 |
| LMArena Chinese | 1427 | 1442 |
| LMArena French | 1431 | 1417 |
| LMArena German | 1413 | 1404 |
| LMArena Japanese | 1378 | 1391 |
| LMArena Korean | 1380 | 1360 |
| LMArena Russian | 1422 | 1423 |
| LMArena Spanish | 1448 | 1411 |
Instruction Following Claude Opus 4.1 leads
Claude Opus 4.1: 75.6 (#58), DeepSeek-R1: 72.0 (#143)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| LMArena Instruction Following | 1435 | 1382 |
| LiveBench Instruction Following | — | 80.5% |
| IFEval | — | 78.4% |
Long Context Too close to call
Claude Opus 4.1: 44.5 (#63), DeepSeek-R1: 45.4 (#36)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1455 | 1391 |
| Fiction.LiveBench | — | 75% |
Writing & Preference Claude Opus 4.1 leads
Claude Opus 4.1: 62.4 (#74), DeepSeek-R1: 61.4 (#88)
| Benchmark | Claude Opus 4.1 | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1419 | 1428 |
| LMArena Creative Writing | 1412 | 1405 |
| Short-Story Creative Writing | 84.7% | 83% |
| LMArena Multi-Turn | 1444 | 1405 |
| EQ-Bench Creative Writing | — | 1500 |
| WildBench | — | 82.8% |
| LiveBench Language | — | 48.5% |
Frequently asked questions
Is Claude Opus 4.1 better than DeepSeek-R1?
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 41.0 on the Noometry Index.
Which is cheaper, Claude Opus 4.1 or DeepSeek-R1?
DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Claude Opus 4.1 lists at $15 and $75.
Is Claude Opus 4.1 or DeepSeek-R1 better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 44.4 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.1 does, with 200K tokens against 164K.
How many benchmarks do Claude Opus 4.1 and DeepSeek-R1 share?
30 benchmarks have published results for both models. Claude Opus 4.1 has 48 scored results on Noometry and DeepSeek-R1 has 52.