# Claude Opus 4.6 vs DeepSeek V4.1 Flash

> Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 52.8 on the Noometry Index. DeepSeek V4.1 Flash costs 38× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-6-vs-deepseek-v4-1-flash
- Last updated: 2026-10-12
- Shared benchmarks: 33

## Summary

- They share 33 benchmarks with published results for both. Claude Opus 4.6 scores higher in 8 categories and DeepSeek V4.1 Flash in 2 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Opus 4.6 leads 51.1 to 31.2.
- The biggest single-benchmark swing is Mystery Game Puzzles: 25% for Claude Opus 4.6 and 43% for DeepSeek V4.1 Flash.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- DeepSeek V4.1 Flash has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 58.2 | 52.8 |
| Rank | 20 | 38 |
| Context | 1M | 1M |
| Input $/M | $5 | $0.15 |
| Output $/M | $25 | $0.60 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.6: 57.2 (#20)
- DeepSeek V4.1 Flash: 52.9 (#32)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena WebDev | 1547 | 1619 |
| LMArena Coding | 1536 | 1506 |
| ALE-Bench | 996.5 | 1,092 |
| SWE-bench Verified | 78.7% | — |
| FrontierCode | 26.6% | — |
| SWE-bench Verified (bash only) | 75.6% | — |
| SWE-bench Multilingual | 72% | — |
| SciCode | — | 51.9% |
| GSO | 41.2% | — |
| WeirdML | 78% | — |
| AlgoTune | 1.47 | — |

## Agentic & Tool Use

- Claude Opus 4.6: 51.1 (#4)
- DeepSeek V4.1 Flash: 31.2 (#69)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| APEX-Agents | 46.3% | 39.5% |
| Terminal-Bench | 79.8% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| GDP.pdf | — | 19.8% |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |

## Reasoning

- Claude Opus 4.6: 57.8 (#23)
- DeepSeek V4.1 Flash: 50.2 (#36)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| NYT Connections (extended) | 92.1% | 89.6% |
| LMArena Hard Prompts | 1527 | 1483 |
| Mystery Game Puzzles | 25% | 43% |
| DTBench | 91.2% | 89.9% |
| LMCA | 55.8% | 47% |
| Epoch Capabilities Index | 155.24 | 154.9 |
| ARC-AGI-2 | 69.2% | — |
| SimpleBench | 67.6% | — |
| Kagi LLM Benchmark | 83.6% | — |
| ARC-AGI-1 | 94% | — |
| CritPt | — | 14.3% |
| Chess Puzzles | 17% | — |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| Surface Evolver Bench | — | 46.3% |
| ForecastBench | 60 | — |

## Math

- Claude Opus 4.6: 63.0 (#31)
- DeepSeek V4.1 Flash: 66.7 (#25)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 67.4% |
| FrontierMath Tier 4 | 26.8% | 26.8% |
| OTIS Mock AIME 2024-2025 | 94.4% | 98.3% |
| ProofBench | 50% | 54% |
| LMArena Math | 1519 | 1477 |
| MathArena Final-Answer Competitions | 78.5% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.6: 61.9 (#26)
- DeepSeek V4.1 Flash: 57.9 (#38)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| GPQA Diamond | 90.5% | 89.8% |
| LMArena Expert | 1546 | 1506 |
| Humanity's Last Exam | 34.4% | — |
| SimpleQA Verified | 47% | — |
| Vectara Hallucination Rate | 12.2% | — |

## Multimodal

- Claude Opus 4.6: 37.3 (#74)
- DeepSeek V4.1 Flash: 39.1 (#61)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Vision | 1316 | 1277 |
| Furniture Assembly | 28.3% | 34.2% |
| LMArena Document | 1507 | — |

## Multilingual

- Claude Opus 4.6: 57.9 (#6)
- DeepSeek V4.1 Flash: 55.0 (#35)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Non-English | 1489 | 1448 |
| LMArena Chinese | 1551 | 1497 |
| LMArena French | 1513 | 1452 |
| LMArena German | 1502 | 1484 |
| LMArena Japanese | 1484 | 1412 |
| LMArena Korean | 1464 | 1452 |
| LMArena Russian | 1497 | 1471 |
| LMArena Spanish | 1510 | 1459 |

## Instruction Following

- Claude Opus 4.6: 79.5 (#4)
- DeepSeek V4.1 Flash: 77.3 (#26)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Instruction Following | 1523 | 1474 |

## Long Context

- Claude Opus 4.6: 48.1 (#13)
- DeepSeek V4.1 Flash: 45.2 (#47)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Longer Query | 1520 | 1475 |
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |

## Writing & Preference

- Claude Opus 4.6: 73.5 (#10)
- DeepSeek V4.1 Flash: 65.4 (#48)

| Benchmark | Claude Opus 4.6 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Text | 1503 | 1462 |
| LMArena Creative Writing | 1505 | 1435 |
| EQ-Bench Creative Writing | 1809 | 1540 |
| LMArena Multi-Turn | 1513 | 1457 |
| EQ-Bench 4 | 1223 | — |

## FAQ

### Is Claude Opus 4.6 better than DeepSeek V4.1 Flash?

Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 52.8 on the Noometry Index. DeepSeek V4.1 Flash costs 38× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.6 or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Claude Opus 4.6 lists at $5 and $25.

### Is Claude Opus 4.6 or DeepSeek V4.1 Flash better for coding?

Claude Opus 4.6 scores higher on coding benchmarks: 57.2 versus 52.9 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do Claude Opus 4.6 and DeepSeek V4.1 Flash share?

33 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and DeepSeek V4.1 Flash has 37.