Model comparison
Qwen3 235B-A22B vs Qwen3-Coder 480B-A35B Instruct
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 38.1 on the Noometry Index.
Last verified . 19 shared benchmarks.
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. Qwen3 235B-A22B scores higher in 8 categories and Qwen3-Coder 480B-A35B Instruct in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 235B-A22B leads 50.4 to 37.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 69.4% for Qwen3 235B-A22B and 49.5% for Qwen3-Coder 480B-A35B Instruct.
- Qwen3 235B-A22B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 131K.
Side by side
| Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 43.5 | 38.1 |
| Released | 2025-04 | 2025-04 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.70 | $1.50 |
| Output $ / M tokens | $2.80 | $7.50 |
| Results tracked | 49 | 25 |
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Category by category
Coding Qwen3 235B-A22B leads
Qwen3 235B-A22B: 44.3 (#75), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 41% | 41.2% |
| LMArena Coding | 1445 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| Aider Polyglot | 59.6% | — |
| LMArena WebDev | — | 1275 |
| SciCode | 42.4% | — |
| GSO | — | 4.9% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Qwen3 235B-A22B leads
Qwen3 235B-A22B: 33.9 (#51), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| Berkeley Function Calling Leaderboard | 52.1% | — |
| Vending-Bench 2 | -11.34 | — |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
Qwen3 235B-A22B: 15.7 (#311), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 69.4% | 49.5% |
| LMArena Hard Prompts | 1433 | 1372 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 31% | — |
| ARC-AGI-1 | 11% | — |
| CritPt | 0% | — |
| Chess Puzzles | 12% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 80.3% | — |
| LMCA | 29.3% | — |
| Epoch Capabilities Index | 143.85 | — |
| ForecastBench | 59.7 | — |
Math Qwen3 235B-A22B leads
Qwen3 235B-A22B: 50.4 (#57), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1432 | 1365 |
| OTIS Mock AIME 2024-2025 | 86.7% | — |
| Omni-MATH | 71.8% | — |
| MATH Level 5 | 68.9% | — |
| FrontierMath (Feb 2025 set) | 8.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3 235B-A22B leads
Qwen3 235B-A22B: 49.6 (#73), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1463 | 1338 |
| GPQA Diamond | 80.1% | — |
| SimpleQA Verified | 40.4% | — |
| MMLU-Pro | 84.4% | — |
| Confabulations | 15.6% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 72.7% | — |
Multilingual Qwen3 235B-A22B leads
Qwen3 235B-A22B: 52.3 (#89), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1409 | 1346 |
| LMArena Chinese | 1481 | 1357 |
| LMArena French | 1445 | 1398 |
| LMArena German | 1433 | 1325 |
| LMArena Japanese | 1399 | 1310 |
| LMArena Korean | 1391 | 1305 |
| LMArena Russian | 1411 | 1366 |
| LMArena Spanish | 1430 | 1360 |
Instruction Following Too close to call
Qwen3 235B-A22B: 72.6 (#136), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1408 | 1355 |
| IFEval | 83.5% | — |
Long Context Qwen3 235B-A22B leads
Qwen3 235B-A22B: 46.1 (#26), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1426 | 1378 |
| Fiction.LiveBench | 75% | — |
Writing & Preference Qwen3 235B-A22B leads
Qwen3 235B-A22B: 59.6 (#108), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Qwen3 235B-A22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1419 | 1357 |
| LMArena Creative Writing | 1384 | 1333 |
| LMArena Multi-Turn | 1432 | 1365 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1366 | — |
| WildBench | 86.6% | — |
Frequently asked questions
Is Qwen3 235B-A22B better than Qwen3-Coder 480B-A35B Instruct?
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 38.1 on the Noometry Index.
Which is cheaper, Qwen3 235B-A22B or Qwen3-Coder 480B-A35B Instruct?
Qwen3 235B-A22B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is Qwen3 235B-A22B or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 131K.
How many benchmarks do Qwen3 235B-A22B and Qwen3-Coder 480B-A35B Instruct share?
19 benchmarks have published results for both models. Qwen3 235B-A22B has 49 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.