Model comparison
GPT-5.5 vs Qwen3.6 Max Preview
GPT-5.5 is the stronger model overall, scoring 63.4 to 51.1 on the Noometry Index. Qwen3.6 Max Preview costs 3.8× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Last verified . 29 shared benchmarks.
Alibaba (Qwen)Summary
- They share 29 benchmarks with published results for both. GPT-5.5 scores higher in 8 categories and Qwen3.6 Max Preview in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.5 leads 72.7 to 40.8.
- The biggest single-benchmark swing is Mystery Game Puzzles: 56% for GPT-5.5 and 19% for Qwen3.6 Max Preview.
- Qwen3.6 Max Preview is cheaper at $1.30 / $7.80 per million input/output tokens, against $5 / $30 for GPT-5.5.
- GPT-5.5 accepts more context: 1.05M tokens versus 262K.
Side by side
| GPT-5.5 | Qwen3.6 Max Preview | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 63.4 | 51.1 |
| Released | 2026-04-23 | 2026-04-20 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $5 | $1.30 |
| Output $ / M tokens | $30 | $7.80 |
| Results tracked | 71 | 29 |
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Category by category
Coding GPT-5.5 leads
GPT-5.5: 58.3 (#13), Qwen3.6 Max Preview: 48.6 (#50)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| SWE-bench Verified | 80.6% | 76.7% |
| LMArena WebDev | 1512 | 1482 |
| LMArena Coding | 1494 | 1472 |
| DeepSWE | 67% | — |
| FrontierCode | 43% | — |
| SciCode | 56.1% | — |
| GSO | 40.2% | — |
| WeirdML | 84.9% | — |
| MirrorCode | 10% | — |
| ALE-Bench | 1,943 | — |
Agentic & Tool Use Not comparable
GPT-5.5: 50.7 (#6), Qwen3.6 Max Preview: —
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| Vending-Bench 2 | 7,524 | 4,254 |
| Terminal-Bench | 84.7% | — |
| APEX-Agents | 55.1% | — |
| OSWorld 2.0 | 13% | — |
| Remote Labor Index | 6.3% | — |
| τ²-bench Banking | 44.6% | — |
| DeepResearch Bench | 54% | — |
| PostTrainBench | 27.2% | — |
| ExploitBench | 47.4% | — |
| GBAEval | 53.2% | — |
| GDP.pdf | 26% | — |
| LMArena Search | 1242 | — |
Reasoning GPT-5.5 leads
GPT-5.5: 72.7 (#8), Qwen3.6 Max Preview: 40.8 (#47)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| SimpleBench | 69% | 63% |
| NYT Connections (extended) | 96.2% | 74.1% |
| Chess Puzzles | 54% | 20% |
| LMArena Hard Prompts | 1489 | 1457 |
| Mystery Game Puzzles | 56% | 19% |
| DTBench | 96% | 87.2% |
| LMCA | 54.3% | 42.5% |
| Epoch Capabilities Index | 159.25 | 149.27 |
| ARC-AGI-2 | 85% | — |
| Kagi LLM Benchmark | 88.8% | — |
| ARC-AGI-1 | 95% | — |
| CritPt | 27.1% | — |
| EBR-Bench | 34.3% | — |
| Surface Evolver Bench | 88.1% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 60.6 | — |
Math GPT-5.5 leads
GPT-5.5: 81.5 (#9), Qwen3.6 Max Preview: 52.2 (#40)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 91.1% |
| LMArena Math | 1486 | 1465 |
| FrontierMath (Feb 2025 set) | 51.7% | 23.1% |
| FrontierMath Tier 4 (v1) | 35.4% | 4.2% |
| FrontierMath (Tiers 1-3) | 85.3% | — |
| FrontierMath Tier 4 | 72.5% | — |
| MathArena Final-Answer Competitions | 94.3% | — |
| ProofBench | 50% | — |
| FrontierMath Erdős | 0% | — |
Knowledge GPT-5.5 leads
GPT-5.5: 64.4 (#14), Qwen3.6 Max Preview: 57.6 (#35)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| GPQA Diamond | 94% | 87.4% |
| SimpleQA Verified | 63% | 52% |
| LMArena Expert | 1508 | 1476 |
| Vectara Hallucination Rate | 9.3% | — |
Multimodal Not comparable
GPT-5.5: 47.1 (#11), Qwen3.6 Max Preview: —
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| LMArena Vision | 1297 | — |
| Blueprint-Bench 2 | 36.2% | — |
| Furniture Assembly | 44.2% | — |
| LMArena Document | 1486 | — |
Multilingual GPT-5.5 leads
GPT-5.5: 56.5 (#19), Qwen3.6 Max Preview: 54.3 (#46)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| LMArena Non-English | 1467 | 1436 |
| LMArena Chinese | 1535 | 1487 |
| LMArena French | 1486 | 1449 |
| LMArena Russian | 1473 | 1444 |
| LMArena Spanish | 1469 | 1452 |
| LMArena German | 1478 | — |
| LMArena Japanese | 1498 | — |
| LMArena Korean | 1461 | — |
Instruction Following GPT-5.5 leads
GPT-5.5: 77.7 (#18), Qwen3.6 Max Preview: 75.8 (#51)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| LMArena Instruction Following | 1479 | 1437 |
Long Context GPT-5.5 leads
GPT-5.5: 48.3 (#12), Qwen3.6 Max Preview: 44.6 (#59)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| LMArena Longer Query | 1484 | 1457 |
| CL-bench Life | 22.2% | — |
Writing & Preference GPT-5.5 leads
GPT-5.5: 72.8 (#13), Qwen3.6 Max Preview: 64.0 (#58)
| Benchmark | GPT-5.5 | Qwen3.6 Max Preview |
|---|---|---|
| LMArena Text | 1471 | 1447 |
| LMArena Creative Writing | 1455 | 1435 |
| LMArena Multi-Turn | 1477 | 1456 |
| EQ-Bench Creative Writing | 1844 | — |
| EQ-Bench 4 | 1315 | — |
Frequently asked questions
Is GPT-5.5 better than Qwen3.6 Max Preview?
GPT-5.5 is the stronger model overall, scoring 63.4 to 51.1 on the Noometry Index. Qwen3.6 Max Preview costs 3.8× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Which is cheaper, GPT-5.5 or Qwen3.6 Max Preview?
Qwen3.6 Max Preview is cheaper. It lists at $1.30 per million input tokens and $7.80 per million output tokens; GPT-5.5 lists at $5 and $30.
Is GPT-5.5 or Qwen3.6 Max Preview better for coding?
GPT-5.5 scores higher on coding benchmarks: 58.3 versus 48.6 in the Noometry coding category.
Which has the bigger context window?
GPT-5.5 does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.5 and Qwen3.6 Max Preview share?
29 benchmarks have published results for both models. GPT-5.5 has 71 scored results on Noometry and Qwen3.6 Max Preview has 29.