Model comparison
GPT-6.1 Sol vs Qwen3.7 Max
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 51.5 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GPT-6.1 Sol scores higher in 6 categories and Qwen3.7 Max in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 49.2.
- The biggest single-benchmark swing is ProofBench: 99% for GPT-6.1 Sol and 26% for Qwen3.7 Max.
- Qwen3.7 Max is cheaper at $2.50 / $7.50 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1M.
Side by side
| GPT-6.1 Sol | Qwen3.7 Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 65.6 | 51.5 |
| Released | 2026-09-29 | 2026-05-19 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $2.50 |
| Output $ / M tokens | $10 | $7.50 |
| Results tracked | 34 | 33 |
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Category by category
Coding GPT-6.1 Sol leads
GPT-6.1 Sol: 63.2 (#8), Qwen3.7 Max: 50.4 (#45)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena WebDev | 1755 | 1515 |
| SciCode | 55.8% | 48.8% |
| LMArena Coding | 1487 | 1498 |
| SWE-bench Verified | — | 77.3% |
| DeepSWE | 75.2% | — |
| FrontierCode | 50.2% | — |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use GPT-6.1 Sol leads
GPT-6.1 Sol: 39.6 (#26), Qwen3.7 Max: 22.1 (#135)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| APEX-Agents | 60% | — |
| GBAEval | — | 0.4% |
| GDP.pdf | 32% | — |
Reasoning GPT-6.1 Sol leads
GPT-6.1 Sol: 81.9 (#2), Qwen3.7 Max: 49.2 (#38)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| NYT Connections (extended) | 95.5% | 85.1% |
| CritPt | 31.7% | 13.4% |
| Chess Puzzles | 61% | 19% |
| EBR-Bench | 54.3% | 9.5% |
| LMArena Hard Prompts | 1466 | 1483 |
| Mystery Game Puzzles | 80% | 32% |
| Epoch Capabilities Index | 166.09 | 153.68 |
| ARC-AGI-2 | 94.2% | — |
| SimpleBench | — | 70.4% |
| ARC-AGI-1 | 98.5% | — |
| DTBench | — | 92.3% |
| LMCA | — | 44% |
Math GPT-6.1 Sol leads
GPT-6.1 Sol: 93.7 (#1), Qwen3.7 Max: 62.4 (#32)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 93.7% | 64.6% |
| FrontierMath Tier 4 | 100% | 34.1% |
| OTIS Mock AIME 2024-2025 | 100% | 95.6% |
| ProofBench | 99% | 26% |
| LMArena Math | 1464 | 1490 |
Knowledge GPT-6.1 Sol leads
GPT-6.1 Sol: 71.8 (#4), Qwen3.7 Max: 61.6 (#28)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | 95.4% | 90.9% |
| SimpleQA Verified | 73.9% | 55.8% |
| LMArena Expert | 1502 | 1488 |
Multimodal Not comparable
GPT-6.1 Sol: 52.7 (#5), Qwen3.7 Max: —
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1288 | — |
| Furniture Assembly | 80% | — |
Multilingual Qwen3.7 Max leads
GPT-6.1 Sol: 54.3 (#46), Qwen3.7 Max: 56.9 (#15)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1438 | 1474 |
| LMArena Chinese | 1477 | 1530 |
| LMArena Russian | 1455 | 1484 |
Instruction Following Too close to call
GPT-6.1 Sol: 77.0 (#29), Qwen3.7 Max: 76.7 (#38)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1468 | 1460 |
Long Context Too close to call
GPT-6.1 Sol: 44.9 (#54), Qwen3.7 Max: 45.4 (#40)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1465 | 1482 |
Writing & Preference Qwen3.7 Max leads
GPT-6.1 Sol: 63.6 (#63), Qwen3.7 Max: 65.0 (#54)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1447 | 1476 |
| LMArena Creative Writing | 1432 | 1449 |
| LMArena Multi-Turn | 1449 | 1481 |
| EQ-Bench 4 | — | 1110 |
Frequently asked questions
Is GPT-6.1 Sol better than Qwen3.7 Max?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 51.5 on the Noometry Index.
Which is cheaper, GPT-6.1 Sol or Qwen3.7 Max?
Qwen3.7 Max is cheaper. It lists at $2.50 per million input tokens and $7.50 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is GPT-6.1 Sol or Qwen3.7 Max better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 50.4 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 1M.
How many benchmarks do GPT-6.1 Sol and Qwen3.7 Max share?
26 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and Qwen3.7 Max has 33.