Model comparison
Claude Opus 4.7 vs Qwen3.8 Max
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 56.8 on the Noometry Index. Qwen3.8 Max costs 3.3× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.
Last verified . 37 shared benchmarks.
Alibaba (Qwen)Summary
- They share 37 benchmarks with published results for both. Claude Opus 4.7 scores higher in 8 categories and Qwen3.8 Max in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Opus 4.7 leads 75.1 to 67.1.
- The biggest single-benchmark swing is NYT Connections (extended): 39% for Claude Opus 4.7 and 88.3% for Qwen3.8 Max.
- Qwen3.8 Max is cheaper at $2 / $6 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
Side by side
| Claude Opus 4.7 | Qwen3.8 Max | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 58.3 | 56.8 |
| Released | 2026-04-14 | 2026-08-02 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $5 | $2 |
| Output $ / M tokens | $25 | $6 |
| Results tracked | 66 | 39 |
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Category by category
Coding Claude Opus 4.7 leads
Claude Opus 4.7: 59.6 (#13), Qwen3.8 Max: 53.5 (#29)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena WebDev | 1558 | 1674 |
| SciCode | 54.5% | 53.2% |
| LMArena Coding | 1518 | 1502 |
| SWE-bench Verified | 83.5% | — |
| DeepSWE | — | 57.5% |
| FrontierCode | 38.5% | — |
| FrontierSWE | — | 17.8% |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |
Agentic & Tool Use Claude Opus 4.7 leads
Claude Opus 4.7: 47.9 (#10), Qwen3.8 Max: 45.4 (#14)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| APEX-Agents | 49.2% | 63.3% |
| τ²-bench Banking | 40.2% | 55.1% |
| GDP.pdf | 21% | 23.2% |
| Terminal-Bench | 80.2% | — |
| OSWorld 2.0 | 18.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Too close to call
Claude Opus 4.7: 53.8 (#29), Qwen3.8 Max: 54.4 (#26)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| NYT Connections (extended) | 39% | 88.3% |
| CritPt | 12% | 20% |
| Chess Puzzles | 30% | 40% |
| LMArena Hard Prompts | 1506 | 1496 |
| Mystery Game Puzzles | 28% | 38% |
| DTBench | 94.7% | 92% |
| LMCA | 52.2% | 46.2% |
| Epoch Capabilities Index | 156.25 | 156.41 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| ARC-AGI-1 | 93.5% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| ForecastBench | 60.3 | — |
Math Qwen3.8 Max leads
Claude Opus 4.7: 66.7 (#26), Qwen3.8 Max: 73.2 (#20)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 74.7% |
| FrontierMath Tier 4 | 31.7% | 46.3% |
| OTIS Mock AIME 2024-2025 | 97.8% | 100% |
| ProofBench | 54% | 58% |
| LMArena Math | 1499 | 1499 |
| MathArena Final-Answer Competitions | 73.6% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Too close to call
Claude Opus 4.7: 62.6 (#23), Qwen3.8 Max: 61.7 (#27)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond | 90.2% | 92.7% |
| SimpleQA Verified | 51.7% | 47.3% |
| LMArena Expert | 1521 | 1507 |
| Humanity's Last Exam | 36.2% | — |
| Vectara Hallucination Rate | 12% | — |
Multimodal Claude Opus 4.7 leads
Claude Opus 4.7: 41.2 (#38), Qwen3.8 Max: 37.2 (#75)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | 1316 | 1314 |
| Furniture Assembly | 33.3% | 20% |
| Blueprint-Bench 2 | 24.5% | — |
| LMArena Document | 1495 | — |
Multilingual Too close to call
Claude Opus 4.7: 57.3 (#10), Qwen3.8 Max: 56.7 (#18)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1480 | 1472 |
| LMArena Chinese | 1531 | 1538 |
| LMArena French | 1503 | 1503 |
| LMArena German | 1495 | 1483 |
| LMArena Japanese | 1472 | 1467 |
| LMArena Korean | 1464 | 1461 |
| LMArena Russian | 1494 | 1481 |
| LMArena Spanish | 1495 | 1492 |
Instruction Following Too close to call
Claude Opus 4.7: 78.4 (#10), Qwen3.8 Max: 77.6 (#17)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1498 | 1479 |
Long Context Too close to call
Claude Opus 4.7: 46.2 (#25), Qwen3.8 Max: 45.6 (#31)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1505 | 1489 |
Writing & Preference Claude Opus 4.7 leads
Claude Opus 4.7: 75.1 (#8), Qwen3.8 Max: 67.1 (#30)
| Benchmark | Claude Opus 4.7 | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1490 | 1483 |
| LMArena Creative Writing | 1486 | 1479 |
| LMArena Multi-Turn | 1505 | 1489 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |
Frequently asked questions
Is Claude Opus 4.7 better than Qwen3.8 Max?
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 56.8 on the Noometry Index. Qwen3.8 Max costs 3.3× 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 Qwen3.8 Max?
Qwen3.8 Max is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Opus 4.7 lists at $5 and $25.
Is Claude Opus 4.7 or Qwen3.8 Max better for coding?
Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 53.5 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Opus 4.7 and Qwen3.8 Max share?
37 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Qwen3.8 Max has 39.