Model comparison
Claude Opus 4.8 vs Qwen3 32B
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 39.2 on the Noometry Index. Qwen3 32B costs 8.2× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Claude Opus 4.8 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 4.8 leads 64.7 to 20.2.
- The biggest single-benchmark swing is LMCA: 57.5% for Claude Opus 4.8 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 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.8 | Qwen3 32B | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 60.7 | 39.2 |
| Released | 2026-05-28 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 16K |
| Input $ / M tokens | $5 | $0.70 |
| Output $ / M tokens | $25 | $2.80 |
| Results tracked | 65 | 26 |
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Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 59.9 (#12), Qwen3 32B: 37.7 (#190)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| SciCode | 53.5% | 35.4% |
| LMArena Coding | 1490 | 1358 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1556 | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Claude Opus 4.8 leads
Claude Opus 4.8: 47.6 (#11), Qwen3 32B: 32.6 (#62)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| APEX-Agents | 48.9% | — |
| Berkeley Function Calling Leaderboard | — | 48.7% |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Claude Opus 4.8 leads
Claude Opus 4.8: 64.7 (#16), Qwen3 32B: 20.2 (#241)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 88.8% | 54.9% |
| CritPt | 20.9% | 0.3% |
| Chess Puzzles | 34% | 5% |
| LMArena Hard Prompts | 1482 | 1334 |
| DTBench | 94.9% | 67.5% |
| LMCA | 57.5% | 17.3% |
| Epoch Capabilities Index | 158.21 | 138.51 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| Mystery Game Puzzles | 36% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 59.9 | — |
Math Claude Opus 4.8 leads
Claude Opus 4.8: 78.4 (#13), Qwen3 32B: 39.7 (#99)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.3% | 66.9% |
| LMArena Math | 1487 | 1399 |
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| ProofBench | 69% | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Claude Opus 4.8 leads
Claude Opus 4.8: 61.3 (#29), Qwen3 32B: 40.0 (#125)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 91% | 65.7% |
| LMArena Expert | 1502 | 1362 |
| SimpleQA Verified | 53% | — |
| Vectara Hallucination Rate | — | 5.9% |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), Qwen3 32B: —
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Claude Opus 4.8 leads
Claude Opus 4.8: 55.2 (#33), Qwen3 32B: 45.6 (#167)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1450 | 1317 |
| LMArena Chinese | 1507 | 1357 |
| LMArena German | 1472 | 1341 |
| LMArena Russian | 1474 | 1311 |
| LMArena French | 1481 | — |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
| LMArena Spanish | 1466 | — |
Instruction Following Claude Opus 4.8 leads
Claude Opus 4.8: 77.4 (#24), Qwen3 32B: 68.9 (#179)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1476 | 1305 |
Long Context Claude Opus 4.8 leads
Claude Opus 4.8: 45.4 (#35), Qwen3 32B: 43.8 (#87)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1483 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference Claude Opus 4.8 leads
Claude Opus 4.8: 72.0 (#16), Qwen3 32B: 52.9 (#163)
| Benchmark | Claude Opus 4.8 | Qwen3 32B |
|---|---|---|
| LMArena Text | 1461 | 1340 |
| LMArena Creative Writing | 1454 | 1297 |
| LMArena Multi-Turn | 1476 | 1331 |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
Frequently asked questions
Is Claude Opus 4.8 better than Qwen3 32B?
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 39.2 on the Noometry Index. Qwen3 32B costs 8.2× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.8 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 4.8 lists at $5 and $25.
Is Claude Opus 4.8 or Qwen3 32B better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.8 does, with 1M tokens against 131K.
How many benchmarks do Claude Opus 4.8 and Qwen3 32B share?
22 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Qwen3 32B has 26.