Model comparison
Qwen3.5 122B-A10B vs Qwen3.8 Max
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 2.7× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
Alibaba (Qwen)Summary
- They share 25 benchmarks with published results for both. Qwen3.5 122B-A10B scores higher in 1 category and Qwen3.8 Max in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.8 Max leads 73.2 to 39.1.
- The biggest single-benchmark swing is NYT Connections (extended): 51.7% for Qwen3.5 122B-A10B and 88.3% for Qwen3.8 Max.
- Qwen3.5 122B-A10B is cheaper at $0.40 / $3.20 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- Qwen3.8 Max accepts more context: 1M tokens versus 262K.
- Qwen3.5 122B-A10B has downloadable open weights; the other is API-only.
Side by side
| Qwen3.5 122B-A10B | Qwen3.8 Max | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 42.1 | 56.8 |
| Released | 2026-02-23 | 2026-08-02 |
| Weights | Open | Proprietary |
| Context window | 262K | 1M |
| Max output | 66K | 131K |
| Input $ / M tokens | $0.40 | $2 |
| Output $ / M tokens | $3.20 | $6 |
| Results tracked | 27 | 39 |
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Category by category
Coding Qwen3.8 Max leads
Qwen3.5 122B-A10B: 39.1 (#162), Qwen3.8 Max: 53.5 (#29)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena WebDev | 1360 | 1674 |
| SciCode | 35.6% | 53.2% |
| LMArena Coding | 1436 | 1502 |
| DeepSWE | — | 57.5% |
| FrontierSWE | — | 17.8% |
Agentic & Tool Use Not comparable
Qwen3.5 122B-A10B: —, Qwen3.8 Max: 45.4 (#14)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| APEX-Agents | — | 63.3% |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
Reasoning Qwen3.8 Max leads
Qwen3.5 122B-A10B: 27.2 (#123), Qwen3.8 Max: 54.4 (#26)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| NYT Connections (extended) | 51.7% | 88.3% |
| CritPt | 0.9% | 20% |
| LMArena Hard Prompts | 1421 | 1496 |
| Mystery Game Puzzles | 17% | 38% |
| DTBench | 84.3% | 92% |
| LMCA | 32.2% | 46.2% |
| Chess Puzzles | — | 40% |
| Thematic Generalization | 51.2% | — |
| Epoch Capabilities Index | — | 156.41 |
Math Qwen3.8 Max leads
Qwen3.5 122B-A10B: 39.1 (#112), Qwen3.8 Max: 73.2 (#20)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Math | 1432 | 1499 |
| FrontierMath (Tiers 1-3) | — | 74.7% |
| FrontierMath Tier 4 | — | 46.3% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 58% |
Knowledge Qwen3.8 Max leads
Qwen3.5 122B-A10B: 38.8 (#142), Qwen3.8 Max: 61.7 (#27)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Expert | 1432 | 1507 |
| GPQA Diamond | — | 92.7% |
| SimpleQA Verified | — | 47.3% |
| Vectara Hallucination Rate | 11.2% | — |
Multimodal Qwen3.5 122B-A10B leads
Qwen3.5 122B-A10B: 39.6 (#57), Qwen3.8 Max: 37.2 (#75)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | 1245 | 1314 |
| Furniture Assembly | — | 20% |
Multilingual Qwen3.8 Max leads
Qwen3.5 122B-A10B: 51.6 (#107), Qwen3.8 Max: 56.7 (#18)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1400 | 1472 |
| LMArena Chinese | 1462 | 1538 |
| LMArena French | 1442 | 1503 |
| LMArena German | 1426 | 1483 |
| LMArena Japanese | 1367 | 1467 |
| LMArena Korean | 1352 | 1461 |
| LMArena Russian | 1400 | 1481 |
| LMArena Spanish | 1424 | 1492 |
Instruction Following Qwen3.8 Max leads
Qwen3.5 122B-A10B: 73.8 (#115), Qwen3.8 Max: 77.6 (#17)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1399 | 1479 |
Long Context Qwen3.8 Max leads
Qwen3.5 122B-A10B: 43.0 (#109), Qwen3.8 Max: 45.6 (#31)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1410 | 1489 |
Writing & Preference Qwen3.8 Max leads
Qwen3.5 122B-A10B: 60.0 (#105), Qwen3.8 Max: 67.1 (#30)
| Benchmark | Qwen3.5 122B-A10B | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1417 | 1483 |
| LMArena Creative Writing | 1368 | 1479 |
| LMArena Multi-Turn | 1416 | 1489 |
Frequently asked questions
Is Qwen3.5 122B-A10B better than Qwen3.8 Max?
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 2.7× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.
Which is cheaper, Qwen3.5 122B-A10B or Qwen3.8 Max?
Qwen3.5 122B-A10B is cheaper. It lists at $0.40 per million input tokens and $3.20 per million output tokens; Qwen3.8 Max lists at $2 and $6.
Is Qwen3.5 122B-A10B or Qwen3.8 Max better for coding?
Qwen3.8 Max scores higher on coding benchmarks: 53.5 versus 39.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3.8 Max does, with 1M tokens against 262K.
How many benchmarks do Qwen3.5 122B-A10B and Qwen3.8 Max share?
25 benchmarks have published results for both models. Qwen3.5 122B-A10B has 27 scored results on Noometry and Qwen3.8 Max has 39.