# Claude Opus 4.7 vs DeepSeek-V3

> Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.5 on the Noometry Index. DeepSeek-V3 costs 25× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-7-vs-deepseek-v3
- Last updated: 2026-10-10
- Shared benchmarks: 31

## Summary

- They share 31 benchmarks with published results for both. Claude Opus 4.7 scores higher in 8 categories and DeepSeek-V3 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 32.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 and 37.8% for DeepSeek-V3.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 58.3 | 39.5 |
| Rank | 19 | 166 |
| Context | 1M | 164K |
| Input $/M | $5 | $0.24 |
| Output $/M | $25 | $0.90 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.6 (#13)
- DeepSeek-V3: 42.3 (#106)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| SciCode | 54.5% | 35.8% |
| WeirdML | 76.4% | 36.1% |
| LMArena Coding | 1518 | 1368 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| Aider Polyglot | — | 55.1% |
| LMArena WebDev | 1558 | — |
| GSO | 44.1% | — |
| BigCodeBench Instruct | — | 50% |
| LiveBench Coding | — | 70.9% |
| MirrorCode | 31.1% | — |
| BigCodeBench Complete | — | 62.2% |
| ALE-Bench | 1,323 | — |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73% |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#10)
- DeepSeek-V3: —

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| 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 | — |
| METR Time Horizons | — | 49.6% |
| Vending-Bench 2 | 10,937 | — |

## Reasoning

- Claude Opus 4.7: 53.8 (#29)
- DeepSeek-V3: 20.5 (#236)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| SimpleBench | 61.7% | 27.2% |
| Kagi LLM Benchmark | 80.7% | 52.3% |
| CritPt | 12% | 0% |
| LMArena Hard Prompts | 1506 | 1365 |
| DTBench | 94.7% | 64.8% |
| LMCA | 52.2% | 15.5% |
| Epoch Capabilities Index | 156.25 | 135.94 |
| ForecastBench | 60.3 | 59.1 |
| ARC-AGI-2 | 75.8% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| Chess Puzzles | 30% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| LiveBench Reasoning | — | 65.8% |
| Mystery Game Puzzles | 28% | — |
| LiveBench Data Analysis | — | 60.9% |
| BIG-Bench Hard | — | 87.5% |
| HellaSwag | — | 88.9% |
| LiveBench | — | 66.9% |
| PIQA | — | 84.7% |
| WinoGrande | — | 85.2% |

## Math

- Claude Opus 4.7: 66.7 (#26)
- DeepSeek-V3: 32.1 (#219)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 37.8% |
| LMArena Math | 1499 | 1373 |
| FrontierMath (Feb 2025 set) | 43.8% | 1.7% |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| Omni-MATH | — | 40.3% |
| LiveBench Math | — | 73.5% |
| MATH Level 5 | — | 75.5% |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#23)
- DeepSeek-V3: 37.5 (#155)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| GPQA Diamond | 90.2% | 67.6% |
| Vectara Hallucination Rate | 12% | 6.1% |
| LMArena Expert | 1521 | 1351 |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 26.1% |
| GPQA (HELM) | — | 53.8% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 87.2% |
| TriviaQA | — | 82.9% |

## Multimodal

- Claude Opus 4.7: 41.2 (#38)
- DeepSeek-V3: —

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| LMArena Vision | 1316 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.3 (#10)
- DeepSeek-V3: 48.5 (#143)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| LMArena Non-English | 1480 | 1358 |
| LMArena Chinese | 1531 | 1391 |
| LMArena French | 1503 | 1385 |
| LMArena German | 1495 | 1374 |
| LMArena Japanese | 1472 | 1333 |
| LMArena Korean | 1464 | 1319 |
| LMArena Russian | 1494 | 1373 |
| LMArena Spanish | 1495 | 1358 |

## Instruction Following

- Claude Opus 4.7: 78.4 (#10)
- DeepSeek-V3: 72.8 (#130)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| LMArena Instruction Following | 1498 | 1345 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | — | 83.2% |

## Long Context

- Claude Opus 4.7: 46.2 (#25)
- DeepSeek-V3: 34.0 (#253)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| LMArena Longer Query | 1505 | 1352 |
| Fiction.LiveBench | — | 50% |

## Writing & Preference

- Claude Opus 4.7: 75.1 (#8)
- DeepSeek-V3: 57.4 (#130)

| Benchmark | Claude Opus 4.7 | DeepSeek-V3 |
|---|---|---|
| LMArena Text | 1490 | 1375 |
| LMArena Creative Writing | 1486 | 1364 |
| EQ-Bench Creative Writing | 1914 | 1472 |
| LMArena Multi-Turn | 1505 | 1389 |
| Short-Story Creative Writing | — | 77% |
| WildBench | — | 83% |
| EQ-Bench 4 | 1311 | — |
| LiveBench Language | — | 49.1% |

## FAQ

### Is Claude Opus 4.7 better than DeepSeek-V3?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.5 on the Noometry Index. DeepSeek-V3 costs 25× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.7 or DeepSeek-V3?

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or DeepSeek-V3 better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 42.3 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 164K.

### How many benchmarks do Claude Opus 4.7 and DeepSeek-V3 share?

31 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and DeepSeek-V3 has 60.