# Claude Opus 4.7 vs Qwen3 32B

> Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.2 on the Noometry Index. Qwen3 32B costs 8.2× 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-qwen3-32b
- Last updated: 2026-10-10
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. Claude Opus 4.7 scores higher in 9 categories and Qwen3 32B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.7 leads 53.8 to 20.2.
- The biggest single-benchmark swing is LMCA: 52.2% for Claude Opus 4.7 and 17.3% for Qwen3 32B.
- Qwen3 32B is cheaper at $0.70 / $2.80 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 58.3 | 39.2 |
| Rank | 19 | 172 |
| Context | 1M | 131K |
| Input $/M | $5 | $0.70 |
| Output $/M | $25 | $2.80 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.6 (#13)
- Qwen3 32B: 37.7 (#190)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| SciCode | 54.5% | 35.4% |
| LMArena Coding | 1518 | 1358 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1558 | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#10)
- Qwen3 32B: 32.6 (#62)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| Berkeley Function Calling Leaderboard | — | 48.7% |
| 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: 53.8 (#29)
- Qwen3 32B: 20.2 (#241)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 80.7% | 54.9% |
| CritPt | 12% | 0.3% |
| Chess Puzzles | 30% | 5% |
| LMArena Hard Prompts | 1506 | 1334 |
| DTBench | 94.7% | 67.5% |
| LMCA | 52.2% | 17.3% |
| Epoch Capabilities Index | 156.25 | 138.51 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.7 (#26)
- Qwen3 32B: 39.7 (#99)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 66.9% |
| LMArena Math | 1499 | 1399 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#23)
- Qwen3 32B: 40.0 (#125)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 90.2% | 65.7% |
| Vectara Hallucination Rate | 12% | 5.9% |
| LMArena Expert | 1521 | 1362 |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |

## Multimodal

- Claude Opus 4.7: 41.2 (#38)
- Qwen3 32B: —

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1316 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.3 (#10)
- Qwen3 32B: 45.6 (#167)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1480 | 1317 |
| LMArena Chinese | 1531 | 1357 |
| LMArena German | 1495 | 1341 |
| LMArena Russian | 1494 | 1311 |
| LMArena French | 1503 | — |
| LMArena Japanese | 1472 | — |
| LMArena Korean | 1464 | — |
| LMArena Spanish | 1495 | — |

## Instruction Following

- Claude Opus 4.7: 78.4 (#10)
- Qwen3 32B: 68.9 (#179)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1498 | 1305 |

## Long Context

- Claude Opus 4.7: 46.2 (#25)
- Qwen3 32B: 43.8 (#87)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1505 | 1327 |
| Fiction.LiveBench | — | 74.2% |

## Writing & Preference

- Claude Opus 4.7: 75.1 (#8)
- Qwen3 32B: 52.9 (#163)

| Benchmark | Claude Opus 4.7 | Qwen3 32B |
|---|---|---|
| LMArena Text | 1490 | 1340 |
| LMArena Creative Writing | 1486 | 1297 |
| LMArena Multi-Turn | 1505 | 1331 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than Qwen3 32B?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.2 on the Noometry Index. Qwen3 32B costs 8.2× 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 Qwen3 32B?

Qwen3 32B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or Qwen3 32B better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 37.7 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 131K.

### How many benchmarks do Claude Opus 4.7 and Qwen3 32B share?

23 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Qwen3 32B has 26.