Model comparison
Claude Opus 4.7 vs DeepSeek LLM 67B
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 24.9 on the Noometry Index.
Last verified . 14 shared benchmarks.
DeepSeekSummary
- They share 14 benchmarks with published results for both. Claude Opus 4.7 scores higher in 8 categories and DeepSeek LLM 67B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4.7 leads 66.7 to 8.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 and 0.8% for DeepSeek LLM 67B.
- DeepSeek LLM 67B has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.7 | DeepSeek LLM 67B | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 58.3 | 24.9 |
| Released | 2026-04-14 | 2023-11-29 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $5 | — |
| Output $ / M tokens | $25 | — |
| Results tracked | 66 | 15 |
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Category by category
Coding Claude Opus 4.7 leads
Claude Opus 4.7: 59.6 (#13), DeepSeek LLM 67B: 31.9 (#278)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Coding | 1518 | 1096 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| LMArena WebDev | 1558 | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.7: 47.9 (#10), DeepSeek LLM 67B: —
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Claude Opus 4.7 leads
Claude Opus 4.7: 53.8 (#29), DeepSeek LLM 67B: 16.5 (#304)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| Chess Puzzles | 30% | 0% |
| LMArena Hard Prompts | 1506 | 1070 |
| Epoch Capabilities Index | 156.25 | 110.5 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| CritPt | 12% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| ForecastBench | 60.3 | — |
Math Claude Opus 4.7 leads
Claude Opus 4.7: 66.7 (#26), DeepSeek LLM 67B: 8.7 (#324)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 0.8% |
| LMArena Math | 1499 | 1108 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| MATH Level 5 | — | 6.4% |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Claude Opus 4.7 leads
Claude Opus 4.7: 62.6 (#23), DeepSeek LLM 67B: 7.0 (#313)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| GPQA Diamond | 90.2% | 24.6% |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| Vectara Hallucination Rate | 12% | — |
| LMArena Expert | 1521 | — |
Multimodal Not comparable
Claude Opus 4.7: 41.2 (#38), DeepSeek LLM 67B: —
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Vision | 1316 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |
Multilingual Claude Opus 4.7 leads
Claude Opus 4.7: 57.3 (#10), DeepSeek LLM 67B: 29.4 (#267)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Non-English | 1480 | 1073 |
| LMArena Chinese | 1531 | 1132 |
| LMArena French | 1503 | — |
| LMArena German | 1495 | — |
| LMArena Japanese | 1472 | — |
| LMArena Korean | 1464 | — |
| LMArena Russian | 1494 | — |
| LMArena Spanish | 1495 | — |
Instruction Following Claude Opus 4.7 leads
Claude Opus 4.7: 78.4 (#10), DeepSeek LLM 67B: 55.4 (#277)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Instruction Following | 1498 | 1079 |
Long Context Claude Opus 4.7 leads
Claude Opus 4.7: 46.2 (#25), DeepSeek LLM 67B: 33.1 (#265)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Longer Query | 1505 | 1092 |
Writing & Preference Claude Opus 4.7 leads
Claude Opus 4.7: 75.1 (#8), DeepSeek LLM 67B: 31.6 (#282)
| Benchmark | Claude Opus 4.7 | DeepSeek LLM 67B |
|---|---|---|
| LMArena Text | 1490 | 1105 |
| LMArena Creative Writing | 1486 | 1067 |
| LMArena Multi-Turn | 1505 | 1082 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |
Frequently asked questions
Is Claude Opus 4.7 better than DeepSeek LLM 67B?
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 24.9 on the Noometry Index.
Is Claude Opus 4.7 or DeepSeek LLM 67B better for coding?
Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 31.9 in the Noometry coding category.
How many benchmarks do Claude Opus 4.7 and DeepSeek LLM 67B share?
14 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and DeepSeek LLM 67B has 15.