Model comparison
GPT-5.1 vs Qwen3.6 Plus
GPT-5.1 is the stronger model overall, scoring 49.0 to 47.5 on the Noometry Index. Qwen3.6 Plus costs 3.1× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 34 shared benchmarks.
Alibaba (Qwen)Summary
- They share 34 benchmarks with published results for both. GPT-5.1 scores higher in 7 categories and Qwen3.6 Plus in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.1 leads 39.8 to 29.3.
- The biggest single-benchmark swing is Chess Puzzles: 32% for GPT-5.1 and 17% for Qwen3.6 Plus.
- Qwen3.6 Plus is cheaper at $0.50 / $3 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- Qwen3.6 Plus accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5.1 | Qwen3.6 Plus | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 49.0 | 47.5 |
| Released | 2025-11-13 | 2026-03-31 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.25 | $0.50 |
| Output $ / M tokens | $10 | $3 |
| Results tracked | 63 | 37 |
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Category by category
Coding GPT-5.1 leads
GPT-5.1: 46.4 (#66), Qwen3.6 Plus: 40.8 (#130)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| SWE-bench Verified | 68% | 57.9% |
| LMArena WebDev | 1395 | 1461 |
| SciCode | 43.3% | 40.7% |
| LMArena Coding | 1454 | 1467 |
| ALE-Bench | 1,192 | 670.15 |
| SWE-bench Verified (bash only) | 66% | — |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
Agentic & Tool Use Not comparable
GPT-5.1: 32.7 (#60), Qwen3.6 Plus: —
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| Vending-Bench 2 | 1,473 | 5,115 |
| Terminal-Bench | 47.6% | — |
| DeepResearch Bench | 42.8% | — |
| LMArena Search | 1199 | — |
Reasoning GPT-5.1 leads
GPT-5.1: 39.8 (#58), Qwen3.6 Plus: 29.3 (#93)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| CritPt | 4.9% | 2.9% |
| Chess Puzzles | 32% | 17% |
| LMArena Hard Prompts | 1457 | 1449 |
| Mystery Game Puzzles | 19% | 12% |
| DTBench | 90.1% | 81.9% |
| LMCA | 43.9% | 33.1% |
| Epoch Capabilities Index | 149.64 | 147.65 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 60.3% |
| ARC-AGI-1 | 72.8% | — |
| EnigmaEval | 11.2% | — |
| Thematic Generalization | — | 59.5% |
| LiveBench Reasoning | 95.8% | — |
| LiveBench Data Analysis | 72.1% | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math Too close to call
GPT-5.1: 52.2 (#51), Qwen3.6 Plus: 51.8 (#54)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 93.3% |
| LMArena Math | 1447 | 1450 |
| FrontierMath (Feb 2025 set) | 31% | 26.2% |
| FrontierMath Tier 4 (v1) | 12.5% | 8.3% |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
Knowledge Qwen3.6 Plus leads
GPT-5.1: 50.6 (#71), Qwen3.6 Plus: 56.1 (#45)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 87.6% | 88.4% |
| SimpleQA Verified | 48% | 44.1% |
| LMArena Expert | 1470 | 1454 |
| Humanity's Last Exam | 23.7% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal Not comparable
GPT-5.1: 44.8 (#19), Qwen3.6 Plus: —
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| LMArena Vision | 1250 | — |
| VPCT | 58.7% | — |
| LMArena Document | 1403 | — |
Multilingual Too close to call
GPT-5.1: 53.8 (#56), Qwen3.6 Plus: 53.3 (#70)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1431 | 1424 |
| LMArena Chinese | 1495 | 1477 |
| LMArena French | 1450 | 1455 |
| LMArena German | 1438 | 1452 |
| LMArena Japanese | 1453 | 1389 |
| LMArena Korean | 1401 | 1379 |
| LMArena Russian | 1435 | 1434 |
| LMArena Spanish | 1433 | 1432 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Qwen3.6 Plus: 75.0 (#74)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1443 | 1425 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Qwen3.6 Plus: 45.2 (#49)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| CL-bench | 23.7% | 20.3% |
| LMArena Longer Query | 1447 | 1439 |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), Qwen3.6 Plus: 62.2 (#82)
| Benchmark | GPT-5.1 | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1443 | 1437 |
| LMArena Creative Writing | 1427 | 1404 |
| LMArena Multi-Turn | 1450 | 1438 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Qwen3.6 Plus?
GPT-5.1 is the stronger model overall, scoring 49.0 to 47.5 on the Noometry Index. Qwen3.6 Plus costs 3.1× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GPT-5.1 or Qwen3.6 Plus?
Qwen3.6 Plus is cheaper. It lists at $0.50 per million input tokens and $3 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Qwen3.6 Plus better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 40.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 Plus does, with 1M tokens against 400K.
How many benchmarks do GPT-5.1 and Qwen3.6 Plus share?
34 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Qwen3.6 Plus has 37.