Model comparison
Claude 3.5 Sonnet vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 34.6 on the Noometry Index.
Last verified . 24 shared benchmarks.
Alibaba (Qwen)Summary
- They share 24 benchmarks with published results for both. Claude 3.5 Sonnet scores higher in 4 categories and Qwen3-30B-A3B in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-30B-A3B leads 37.4 to 19.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 8.5% for Claude 3.5 Sonnet and 70.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B has downloadable open weights; the other is API-only.
Side by side
| Claude 3.5 Sonnet | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 34.6 | 38.9 |
| Released | 2024-06-20 | 2025-04-28 |
| Weights | Proprietary | Open |
| Context window | — | 41K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.12 |
| Output $ / M tokens | — | $0.50 |
| Results tracked | 60 | 32 |
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Category by category
Coding Claude 3.5 Sonnet leads
Claude 3.5 Sonnet: 39.0 (#165), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| WeirdML | 40% | 29.8% |
| LMArena Coding | 1342 | 1416 |
| Aider Polyglot | 51.6% | — |
| SciCode | — | 33.3% |
| GSO | 4.6% | — |
| BigCodeBench Instruct | 46.8% | — |
| LiveBench Coding | 67.1% | — |
| BigCodeBench Complete | 58.6% | — |
| CadEval | 48% | — |
| HumanEval+ | 81.7% | — |
| MBPP+ | 74.3% | — |
Agentic & Tool Use Claude 3.5 Sonnet leads
Claude 3.5 Sonnet: 32.3 (#67), Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
| TheAgentCompany | 24% | — |
| Cybench | 17.5% | — |
| BALROG | 32.6% | — |
| METR Time Horizons | 45.2% | — |
Reasoning Too close to call
Claude 3.5 Sonnet: 23.1 (#183), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Hard Prompts | 1305 | 1398 |
| DTBench | 67.8% | 69.3% |
| Epoch Capabilities Index | 133.55 | 139.63 |
| SimpleBench | 41.4% | — |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 8% |
| EnigmaEval | 0.9% | — |
| LiveBench Reasoning | 56.7% | — |
| LiveBench Data Analysis | 55% | — |
| LMCA | — | 22.4% |
| ForecastBench | 60.7 | — |
| LiveBench | 59% | — |
Math Qwen3-30B-A3B leads
Claude 3.5 Sonnet: 19.2 (#288), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 70.3% |
| LMArena Math | 1307 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| Omni-MATH | 27.6% | — |
| LiveBench Math | 52.3% | — |
| MATH Level 5 | 56.9% | — |
| FrontierMath (Feb 2025 set) | 2.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3-30B-A3B leads
Claude 3.5 Sonnet: 28.6 (#245), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 55.3% | 70.1% |
| Confabulations | 19.9% | 12.3% |
| LMArena Expert | 1265 | 1396 |
| Humanity's Last Exam | 4.1% | — |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 56.5% | — |
| MMLU | 87.3% | — |
Multimodal Not comparable
Claude 3.5 Sonnet: 26.5 (#120), Qwen3-30B-A3B: —
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Vision | 1125 | — |
| Video-MME | 60% | — |
| GeoBench | 62% | — |
| VPCT | 33% | — |
Multilingual Qwen3-30B-A3B leads
Claude 3.5 Sonnet: 43.2 (#185), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1283 | 1372 |
| LMArena Chinese | 1272 | 1433 |
| LMArena French | 1305 | 1418 |
| LMArena German | 1297 | 1380 |
| LMArena Japanese | 1234 | 1337 |
| LMArena Korean | 1200 | 1331 |
| LMArena Russian | 1306 | 1370 |
| LMArena Spanish | 1290 | 1404 |
Instruction Following Qwen3-30B-A3B leads
Claude 3.5 Sonnet: 68.8 (#182), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1297 | 1363 |
| LiveBench Instruction Following | 69.3% | — |
| IFEval | 85.5% | — |
Long Context Claude 3.5 Sonnet leads
Claude 3.5 Sonnet: 39.9 (#167), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1311 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Qwen3-30B-A3B leads
Claude 3.5 Sonnet: 52.9 (#164), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Claude 3.5 Sonnet | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1298 | 1384 |
| LMArena Creative Writing | 1292 | 1317 |
| Short-Story Creative Writing | 80.3% | 75.3% |
| LMArena Multi-Turn | 1326 | 1378 |
| EQ-Bench Creative Writing | 1451 | — |
| WildBench | 79.2% | — |
| LiveBench Language | 53.8% | — |
Frequently asked questions
Is Claude 3.5 Sonnet better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 34.6 on the Noometry Index.
Is Claude 3.5 Sonnet or Qwen3-30B-A3B better for coding?
Claude 3.5 Sonnet scores higher on coding benchmarks: 39.0 versus 37.5 in the Noometry coding category.
How many benchmarks do Claude 3.5 Sonnet and Qwen3-30B-A3B share?
24 benchmarks have published results for both models. Claude 3.5 Sonnet has 60 scored results on Noometry and Qwen3-30B-A3B has 32.