# Claude Opus 5.5 vs DeepSeek V4 Pro

> Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 54.2 on the Noometry Index. DeepSeek V4 Pro costs 15× 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-v4-pro
- Last updated: 2026-10-10
- Shared benchmarks: 29

## Summary

- They share 29 benchmarks with published results for both. Claude Opus 5.5 scores higher in 9 categories and DeepSeek V4 Pro in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 5.5 leads 92.4 to 64.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 95% for Claude Opus 5.5 and 26.8% for DeepSeek V4 Pro.
- DeepSeek V4 Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 68.5 | 54.2 |
| Rank | 3 | 28 |
| Context | 1M | 1M |
| Input $/M | $4 | $0.43 |
| Output $/M | $20 | $0.87 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 5.5: 71.4 (#1)
- DeepSeek V4 Pro: 52.2 (#31)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| FrontierCode | 54.4% | 28.6% |
| LMArena WebDev | 1820 | 1582 |
| SciCode | 66.9% | 51% |
| LMArena Coding | 1545 | 1470 |
| SWE-bench Verified | — | 77.6% |
| CursorBench | 57.8% | — |
| FrontierSWE | 62.3% | — |
| WeirdML | — | 66.2% |
| MirrorCode | 77.4% | — |
| ALE-Bench | — | 1,403 |

## Agentic & Tool Use

- Claude Opus 5.5: 45.3 (#13)
- DeepSeek V4 Pro: 32.7 (#54)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| APEX-Agents | 73.5% | 47.3% |
| GDP.pdf | 30.6% | — |
| Vending-Bench 2 | — | 3,285 |

## Reasoning

- Claude Opus 5.5: 79.5 (#2)
- DeepSeek V4 Pro: 56.4 (#22)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| ARC-AGI-2 | 92.5% | 61.3% |
| NYT Connections (extended) | 88.5% | 91.3% |
| ARC-AGI-1 | 97.5% | 90.5% |
| CritPt | 31.7% | 18% |
| LMArena Hard Prompts | 1545 | 1461 |
| Mystery Game Puzzles | 71% | 43% |
| DTBench | 98.9% | 93.9% |
| LMCA | 68.2% | 45.5% |
| Kagi LLM Benchmark | — | 53.5% |
| Chess Puzzles | — | 47% |
| EBR-Bench | 71.4% | — |
| Surface Evolver Bench | — | 40% |
| Epoch Capabilities Index | — | 155.39 |
| ForecastBench | — | 56.1 |

## Math

- Claude Opus 5.5: 92.4 (#2)
- DeepSeek V4 Pro: 64.6 (#24)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 91.2% | 64.6% |
| FrontierMath Tier 4 | 95% | 26.8% |
| OTIS Mock AIME 2024-2025 | 100% | 98.6% |
| ProofBench | 100% | 50% |
| MathArena Final-Answer Competitions | — | 76.6% |
| LMArena Math | — | 1455 |

## Knowledge

- Claude Opus 5.5: 66.6 (#9)
- DeepSeek V4 Pro: 59.5 (#28)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| GPQA Diamond | 90.6% | 91.7% |
| SimpleQA Verified | 72.2% | 52.9% |
| LMArena Expert | 1564 | 1463 |
| Vectara Hallucination Rate | — | 8.6% |

## Multimodal

- Claude Opus 5.5: 56.5 (#2)
- DeepSeek V4 Pro: —

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| Furniture Assembly | 83.3% | — |

## Multilingual

- Claude Opus 5.5: 59.8 (#1)
- DeepSeek V4 Pro: 54.5 (#44)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| LMArena Non-English | 1513 | 1438 |
| LMArena Chinese | 1572 | 1486 |
| LMArena Russian | 1532 | 1452 |
| LMArena French | — | 1473 |
| LMArena German | — | 1458 |
| LMArena Japanese | — | 1448 |
| LMArena Korean | — | 1452 |
| LMArena Spanish | — | 1457 |

## Instruction Following

- Claude Opus 5.5: 80.1 (#2)
- DeepSeek V4 Pro: 76.3 (#44)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| LMArena Instruction Following | 1535 | 1448 |

## Long Context

- Claude Opus 5.5: 47.3 (#18)
- DeepSeek V4 Pro: 45.0 (#49)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| LMArena Longer Query | 1540 | 1459 |
| CL-bench Life | — | 13.5% |

## Writing & Preference

- Claude Opus 5.5: 78.7 (#3)
- DeepSeek V4 Pro: 65.6 (#45)

| Benchmark | Claude Opus 5.5 | DeepSeek V4 Pro |
|---|---|---|
| LMArena Text | 1518 | 1451 |
| LMArena Creative Writing | 1538 | 1446 |
| EQ-Bench Creative Writing | 2050 | 1553 |
| LMArena Multi-Turn | 1520 | 1467 |
| EQ-Bench 4 | — | 1166 |

## FAQ

### Is Claude Opus 5.5 better than DeepSeek V4 Pro?

Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 54.2 on the Noometry Index. DeepSeek V4 Pro costs 15× 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 V4 Pro?

DeepSeek V4 Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Claude Opus 5.5 lists at $4 and $20.

### Is Claude Opus 5.5 or DeepSeek V4 Pro better for coding?

Claude Opus 5.5 scores higher on coding benchmarks: 71.4 versus 52.2 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do Claude Opus 5.5 and DeepSeek V4 Pro share?

29 benchmarks have published results for both models. Claude Opus 5.5 has 35 scored results on Noometry and DeepSeek V4 Pro has 48.