Model comparison
GPT-6.1 Sol vs Qwen3.7 Plus
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 45.3 on the Noometry Index. Qwen3.7 Plus costs 5.7× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. GPT-6.1 Sol scores higher in 8 categories and Qwen3.7 Plus in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 50.5.
- The biggest single-benchmark swing is Mystery Game Puzzles: 80% for GPT-6.1 Sol and 17% for Qwen3.7 Plus.
- Qwen3.7 Plus is cheaper at $0.40 / $1.60 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 Plus | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 65.6 | 45.3 |
| Released | 2026-09-29 | 2026-06-02 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $0.40 |
| Output $ / M tokens | $10 | $1.60 |
| Results tracked | 34 | 32 |
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Category by category
Coding GPT-6.1 Sol leads
GPT-6.1 Sol: 63.2 (#8), Qwen3.7 Plus: 36.6 (#206)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| FrontierCode | 50.2% | 10.2% |
| SciCode | 55.8% | 45.5% |
| LMArena Coding | 1487 | 1473 |
| DeepSWE | 75.2% | — |
| LMArena WebDev | 1755 | — |
Agentic & Tool Use GPT-6.1 Sol leads
GPT-6.1 Sol: 39.6 (#26), Qwen3.7 Plus: 21.4 (#138)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| APEX-Agents | 60% | — |
| OSWorld 2.0 | — | 2.8% |
| GDP.pdf | 32% | — |
Reasoning GPT-6.1 Sol leads
GPT-6.1 Sol: 81.9 (#2), Qwen3.7 Plus: 39.3 (#59)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| NYT Connections (extended) | 95.5% | 74.8% |
| CritPt | 31.7% | 9.1% |
| Chess Puzzles | 61% | 24% |
| LMArena Hard Prompts | 1466 | 1460 |
| Mystery Game Puzzles | 80% | 17% |
| Epoch Capabilities Index | 166.09 | 147.37 |
| ARC-AGI-2 | 94.2% | — |
| ARC-AGI-1 | 98.5% | — |
| EBR-Bench | 54.3% | — |
| DTBench | — | 84% |
| LMCA | — | 37.6% |
Math GPT-6.1 Sol leads
GPT-6.1 Sol: 93.7 (#1), Qwen3.7 Plus: 50.5 (#56)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| FrontierMath (Tiers 1-3) | 93.7% | 34.4% |
| OTIS Mock AIME 2024-2025 | 100% | 93.3% |
| LMArena Math | 1464 | 1466 |
| FrontierMath Tier 4 | 100% | — |
| ProofBench | 99% | — |
Knowledge GPT-6.1 Sol leads
GPT-6.1 Sol: 71.8 (#4), Qwen3.7 Plus: 54.9 (#51)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| GPQA Diamond | 95.4% | 87.9% |
| LMArena Expert | 1502 | 1467 |
| SimpleQA Verified | 73.9% | — |
Multimodal GPT-6.1 Sol leads
GPT-6.1 Sol: 52.7 (#5), Qwen3.7 Plus: 41.8 (#33)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| LMArena Vision | 1288 | 1279 |
| Furniture Assembly | 80% | — |
| LMArena Document | — | 1444 |
Multilingual Too close to call
GPT-6.1 Sol: 54.3 (#46), Qwen3.7 Plus: 54.8 (#38)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| LMArena Non-English | 1438 | 1445 |
| LMArena Chinese | 1477 | 1510 |
| LMArena Russian | 1455 | 1457 |
| LMArena French | — | 1473 |
| LMArena German | — | 1471 |
| LMArena Japanese | — | 1413 |
| LMArena Korean | — | 1415 |
| LMArena Spanish | — | 1457 |
Instruction Following GPT-6.1 Sol leads
GPT-6.1 Sol: 77.0 (#29), Qwen3.7 Plus: 75.8 (#52)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| LMArena Instruction Following | 1468 | 1440 |
Long Context Too close to call
GPT-6.1 Sol: 44.9 (#54), Qwen3.7 Plus: 44.5 (#65)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| LMArena Longer Query | 1465 | 1455 |
Writing & Preference Too close to call
GPT-6.1 Sol: 63.6 (#63), Qwen3.7 Plus: 64.3 (#56)
| Benchmark | GPT-6.1 Sol | Qwen3.7 Plus |
|---|---|---|
| LMArena Text | 1447 | 1455 |
| LMArena Creative Writing | 1432 | 1439 |
| LMArena Multi-Turn | 1449 | 1460 |
Frequently asked questions
Is GPT-6.1 Sol better than Qwen3.7 Plus?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 45.3 on the Noometry Index. Qwen3.7 Plus costs 5.7× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6.1 Sol or Qwen3.7 Plus?
Qwen3.7 Plus is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is GPT-6.1 Sol or Qwen3.7 Plus better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 36.6 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 Plus share?
23 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and Qwen3.7 Plus has 32.