Model comparison
Qwen3.5 122B-A10B vs Qwen3-Coder 480B-A35B Instruct
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 38.1 on the Noometry Index.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Qwen3.5 122B-A10B scores higher in 8 categories and Qwen3-Coder 480B-A35B Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 122B-A10B leads 60.0 to 55.3.
- Qwen3.5 122B-A10B is cheaper at $0.40 / $3.20 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
Side by side
| Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 42.1 | 38.1 |
| Released | 2026-02-23 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.40 | $1.50 |
| Output $ / M tokens | $3.20 | $7.50 |
| Results tracked | 27 | 25 |
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Category by category
Coding Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 39.1 (#162), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena WebDev | 1360 | 1275 |
| LMArena Coding | 1436 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| SciCode | 35.6% | — |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
Qwen3.5 122B-A10B: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 27.2 (#123), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1421 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
| NYT Connections (extended) | 51.7% | — |
| CritPt | 0.9% | — |
| Thematic Generalization | 51.2% | — |
| Mystery Game Puzzles | 17% | — |
| DTBench | 84.3% | — |
| LMCA | 32.2% | — |
Math Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 39.1 (#112), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1432 | 1365 |
Knowledge Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 38.8 (#142), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1432 | 1338 |
| Vectara Hallucination Rate | 11.2% | — |
Multimodal Not comparable
Qwen3.5 122B-A10B: 39.6 (#57), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1245 | — |
Multilingual Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 51.6 (#107), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1400 | 1346 |
| LMArena Chinese | 1462 | 1357 |
| LMArena French | 1442 | 1398 |
| LMArena German | 1426 | 1325 |
| LMArena Japanese | 1367 | 1310 |
| LMArena Korean | 1352 | 1305 |
| LMArena Russian | 1400 | 1366 |
| LMArena Spanish | 1424 | 1360 |
Instruction Following Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 73.8 (#115), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1399 | 1355 |
Long Context Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 43.0 (#109), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1410 | 1378 |
Writing & Preference Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 60.0 (#105), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Qwen3.5 122B-A10B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1417 | 1357 |
| LMArena Creative Writing | 1368 | 1333 |
| LMArena Multi-Turn | 1416 | 1365 |
Frequently asked questions
Is Qwen3.5 122B-A10B better than Qwen3-Coder 480B-A35B Instruct?
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 38.1 on the Noometry Index.
Which is cheaper, Qwen3.5 122B-A10B or Qwen3-Coder 480B-A35B Instruct?
Qwen3.5 122B-A10B is cheaper. It lists at $0.40 per million input tokens and $3.20 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is Qwen3.5 122B-A10B or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3.5 122B-A10B scores higher on coding benchmarks: 39.1 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Qwen3.5 122B-A10B and Qwen3-Coder 480B-A35B Instruct share?
18 benchmarks have published results for both models. Qwen3.5 122B-A10B has 27 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.