# Claude Opus 5.5 vs DeepSeek-V3

> Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 39.2 on the Noometry Index. DeepSeek-V3 costs 20× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-5-5-vs-deepseek-v3
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Claude Opus 5.5 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 5.5 leads 92.4 to 30.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for Claude Opus 5.5 and 37.8% for DeepSeek-V3.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- Claude Opus 5.5 accepts more context: 1M tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 68.5 | 39.2 |
| Rank | 3 | 157 |
| Context | 1M | 164K |
| Input $/M | $4 | $0.24 |
| Output $/M | $20 | $0.90 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 5.5: 71.4 (#1)
- DeepSeek-V3: 41.9 (#99)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| SciCode | 66.9% | 35.8% |
| LMArena Coding | 1545 | 1368 |
| FrontierCode | 54.4% | — |
| Aider Polyglot | — | 55.1% |
| CursorBench | 57.8% | — |
| LMArena WebDev | 1820 | — |
| FrontierSWE | 62.3% | — |
| WeirdML | — | 36.1% |
| BigCodeBench Instruct | — | 50% |
| LiveBench Coding | — | 70.9% |
| MirrorCode | 77.4% | — |
| BigCodeBench Complete | — | 62.2% |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73% |

## Agentic & Tool Use

- Claude Opus 5.5: 45.3 (#13)
- DeepSeek-V3: —

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| APEX-Agents | 73.5% | — |
| GDP.pdf | 30.6% | — |
| METR Time Horizons | — | 49.6% |

## Reasoning

- Claude Opus 5.5: 79.5 (#2)
- DeepSeek-V3: 20.0 (#226)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| CritPt | 31.7% | 0% |
| LMArena Hard Prompts | 1545 | 1365 |
| DTBench | 98.9% | 64.8% |
| LMCA | 68.2% | 15.5% |
| ARC-AGI-2 | 92.5% | — |
| SimpleBench | — | 27.2% |
| Kagi LLM Benchmark | — | 52.3% |
| NYT Connections (extended) | 88.5% | — |
| ARC-AGI-1 | 97.5% | — |
| EBR-Bench | 71.4% | — |
| LiveBench Reasoning | — | 65.8% |
| Mystery Game Puzzles | 71% | — |
| LiveBench Data Analysis | — | 60.9% |
| BIG-Bench Hard | — | 87.5% |
| Epoch Capabilities Index | — | 135.95 |
| ForecastBench | — | 59.1 |
| HellaSwag | — | 88.9% |
| LiveBench | — | 66.9% |
| PIQA | — | 84.7% |
| WinoGrande | — | 85.2% |

## Math

- Claude Opus 5.5: 92.4 (#2)
- DeepSeek-V3: 30.4 (#208)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 37.8% |
| FrontierMath (Tiers 1-3) | 91.2% | — |
| FrontierMath Tier 4 | 95% | — |
| ProofBench | 100% | — |
| Omni-MATH | — | 40.3% |
| LiveBench Math | — | 73.5% |
| LMArena Math | — | 1373 |
| MATH Level 5 | — | 75.5% |
| FrontierMath (Feb 2025 set) | — | 1.7% |

## Knowledge

- Claude Opus 5.5: 66.6 (#9)
- DeepSeek-V3: 37.5 (#147)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| GPQA Diamond | 90.6% | 67.6% |
| LMArena Expert | 1564 | 1352 |
| SimpleQA Verified | 72.2% | — |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 26.1% |
| Vectara Hallucination Rate | — | 6.1% |
| GPQA (HELM) | — | 53.8% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 87.2% |
| TriviaQA | — | 82.9% |

## Multimodal

- Claude Opus 5.5: 56.5 (#2)
- DeepSeek-V3: —

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| Furniture Assembly | 83.3% | — |

## Multilingual

- Claude Opus 5.5: 59.8 (#1)
- DeepSeek-V3: 48.8 (#138)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| LMArena Non-English | 1513 | 1358 |
| LMArena Chinese | 1572 | 1390 |
| LMArena Russian | 1532 | 1372 |
| LMArena French | — | 1386 |
| LMArena German | — | 1374 |
| LMArena Japanese | — | 1333 |
| LMArena Korean | — | 1321 |
| LMArena Spanish | — | 1358 |

## Instruction Following

- Claude Opus 5.5: 80.1 (#2)
- DeepSeek-V3: 73.0 (#125)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| LMArena Instruction Following | 1535 | 1345 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | — | 83.2% |

## Long Context

- Claude Opus 5.5: 47.3 (#18)
- DeepSeek-V3: 34.0 (#248)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| LMArena Longer Query | 1540 | 1353 |
| Fiction.LiveBench | — | 50% |

## Writing & Preference

- Claude Opus 5.5: 78.7 (#3)
- DeepSeek-V3: 57.6 (#124)

| Benchmark | Claude Opus 5.5 | DeepSeek-V3 |
|---|---|---|
| LMArena Text | 1518 | 1375 |
| LMArena Creative Writing | 1538 | 1364 |
| EQ-Bench Creative Writing | 2050 | 1472 |
| LMArena Multi-Turn | 1520 | 1389 |
| Short-Story Creative Writing | — | 77% |
| WildBench | — | 83% |
| LiveBench Language | — | 49.1% |

## FAQ

### Is Claude Opus 5.5 better than DeepSeek-V3?

Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 39.2 on the Noometry Index. DeepSeek-V3 costs 20× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 5.5 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 5.5 lists at $4 and $20.

### Is Claude Opus 5.5 or DeepSeek-V3 better for coding?

Claude Opus 5.5 scores higher on coding benchmarks: 71.4 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 5.5 does, with 1M tokens against 164K.

### How many benchmarks do Claude Opus 5.5 and DeepSeek-V3 share?

18 benchmarks have published results for both models. Claude Opus 5.5 has 35 scored results on Noometry and DeepSeek-V3 has 60.