Model comparison
Claude Sonnet 4.5 vs DeepSeek LLM 67B
Claude Sonnet 4.5 is the stronger model overall, scoring 44.0 to 24.8 on the Noometry Index.
Last verified . 15 shared benchmarks.
DeepSeekSummary
- They share 15 benchmarks with published results for both. Claude Sonnet 4.5 scores higher in 8 categories and DeepSeek LLM 67B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Claude Sonnet 4.5 leads 48.4 to 7.1.
- The biggest single-benchmark swing is MATH Level 5: 97.7% for Claude Sonnet 4.5 and 6.4% for DeepSeek LLM 67B.
- DeepSeek LLM 67B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.5 | DeepSeek LLM 67B | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 44.0 | 24.8 |
| Released | 2025-09-29 | 2023-11-29 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 64K | — |
| Input $ / M tokens | $3 | — |
| Output $ / M tokens | $15 | — |
| Results tracked | 73 | 15 |
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Category by category
Coding Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 47.8 (#54), DeepSeek LLM 67B: 31.3 (#273)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Coding | 1489 | 1096 |
| SWE-bench Verified | 71.3% | — |
| SWE-bench Verified (bash only) | 71.4% | — |
| LMArena WebDev | 1393 | — |
| SWE-bench Multilingual | 67% | — |
| SciCode | 44.7% | — |
| GSO | 14.7% | — |
| WeirdML | 47.7% | — |
| ALE-Bench | 796.15 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.5: 38.1 (#30), DeepSeek LLM 67B: —
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| Terminal-Bench | 46.5% | — |
| Berkeley Function Calling Leaderboard | 73.2% | — |
| GDPval | 42.5% | — |
| Remote Labor Index | 2.1% | — |
| τ²-bench Airline | 72% | — |
| τ²-bench Banking | 25.3% | — |
| τ²-bench Retail | 72.4% | — |
| τ²-bench Telecom | 84.9% | — |
| Cybench | 60% | — |
| DeepResearch Bench | 52.6% | — |
| OSWorld | 62.9% | — |
| LMArena Search | 1159 | — |
| METR Time Horizons | 67.4% | — |
| Vending-Bench 2 | 3,839 | — |
Reasoning Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 26.9 (#113), DeepSeek LLM 67B: 15.9 (#300)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| Chess Puzzles | 12% | 0% |
| LMArena Hard Prompts | 1462 | 1070 |
| Epoch Capabilities Index | 146.84 | 110.54 |
| ARC-AGI-2 | 13.6% | — |
| SimpleBench | 54.3% | — |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | 37.3% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 1.1% | — |
| EnigmaEval | 6% | — |
| EBR-Bench | 2.4% | — |
| Mystery Game Puzzles | 17% | — |
| DTBench | 83.2% | — |
| LMCA | 38.8% | — |
| ForecastBench | 61.9 | — |
Math Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 31.9 (#190), DeepSeek LLM 67B: 8.1 (#318)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 77.8% | 0.8% |
| LMArena Math | 1448 | 1108 |
| MATH Level 5 | 97.7% | 6.4% |
| FrontierMath (Tiers 1-3) | 23.9% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 19% | — |
| Omni-MATH | 55.3% | — |
| FrontierMath (Feb 2025 set) | 15.2% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 48.4 (#70), DeepSeek LLM 67B: 7.1 (#308)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| GPQA Diamond | 82.3% | 24.6% |
| Humanity's Last Exam | 13.7% | — |
| SimpleQA Verified | 30.7% | — |
| MMLU-Pro | 86.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 68.6% | — |
| LMArena Expert | 1483 | — |
Multimodal Not comparable
Claude Sonnet 4.5: 34.1 (#84), DeepSeek LLM 67B: —
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| VPCT | 39.8% | — |
| LMArena Document | 1450 | — |
Multilingual Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 53.6 (#65), DeepSeek LLM 67B: 29.5 (#262)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Non-English | 1425 | 1073 |
| LMArena Chinese | 1459 | 1132 |
| LMArena French | 1459 | — |
| LMArena German | 1427 | — |
| LMArena Japanese | 1390 | — |
| LMArena Korean | 1403 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1457 | — |
Instruction Following Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 75.2 (#74), DeepSeek LLM 67B: 55.7 (#272)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Instruction Following | 1459 | 1079 |
| IFEval | 85% | — |
Long Context Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 45.2 (#45), DeepSeek LLM 67B: 33.1 (#260)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Longer Query | 1476 | 1092 |
Writing & Preference Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 66.7 (#33), DeepSeek LLM 67B: 31.8 (#277)
| Benchmark | Claude Sonnet 4.5 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Text | 1439 | 1105 |
| LMArena Creative Writing | 1442 | 1067 |
| LMArena Multi-Turn | 1465 | 1082 |
| EQ-Bench Creative Writing | 1678 | — |
| WildBench | 85.4% | — |
Frequently asked questions
Is Claude Sonnet 4.5 better than DeepSeek LLM 67B?
Claude Sonnet 4.5 is the stronger model overall, scoring 44.0 to 24.8 on the Noometry Index.
Is Claude Sonnet 4.5 or DeepSeek LLM 67B better for coding?
Claude Sonnet 4.5 scores higher on coding benchmarks: 47.8 versus 31.3 in the Noometry coding category.
How many benchmarks do Claude Sonnet 4.5 and DeepSeek LLM 67B share?
15 benchmarks have published results for both models. Claude Sonnet 4.5 has 73 scored results on Noometry and DeepSeek LLM 67B has 15.