Model comparison
Gemini 3.7 Flash vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 2.7× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 33 shared benchmarks.
Summary
- They share 33 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 5 categories and GPT-6.1 Sol in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 69.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 36.6% for Gemini 3.7 Flash and 100% for GPT-6.1 Sol.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 3.7 Flash | GPT-6.1 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 59.8 | 65.6 |
| Released | 2026-08-13 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $2 |
| Output $ / M tokens | $3.75 | $10 |
| Results tracked | 44 | 34 |
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Category by category
Coding GPT-6.1 Sol leads
Gemini 3.7 Flash: 56.2 (#22), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| DeepSWE | 65.5% | 75.2% |
| FrontierCode | 43.6% | 50.2% |
| LMArena WebDev | 1592 | 1755 |
| SciCode | 59.8% | 55.8% |
| LMArena Coding | 1497 | 1487 |
| FrontierSWE | 20.3% | — |
| ALE-Bench | 904.3 | — |
Agentic & Tool Use Gemini 3.7 Flash leads
Gemini 3.7 Flash: 42.1 (#19), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | 67.8% | 60% |
| GDP.pdf | 23.8% | 32% |
| Remote Labor Index | 5% | — |
Reasoning GPT-6.1 Sol leads
Gemini 3.7 Flash: 70.0 (#15), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| ARC-AGI-2 | 84.6% | 94.2% |
| NYT Connections (extended) | 94% | 95.5% |
| ARC-AGI-1 | 95.5% | 98.5% |
| CritPt | 14.3% | 31.7% |
| Chess Puzzles | 47% | 61% |
| LMArena Hard Prompts | 1494 | 1466 |
| Mystery Game Puzzles | 37% | 80% |
| Epoch Capabilities Index | 157.27 | 166.09 |
| EBR-Bench | — | 54.3% |
| DTBench | 96.8% | — |
| LMCA | 50.4% | — |
Math GPT-6.1 Sol leads
Gemini 3.7 Flash: 69.6 (#23), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | 93.7% |
| FrontierMath Tier 4 | 36.6% | 100% |
| OTIS Mock AIME 2024-2025 | 97.2% | 100% |
| ProofBench | 58% | 99% |
| LMArena Math | 1507 | 1464 |
Knowledge GPT-6.1 Sol leads
Gemini 3.7 Flash: 69.7 (#5), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 94.8% | 95.4% |
| SimpleQA Verified | 69.2% | 73.9% |
| LMArena Expert | 1508 | 1502 |
Multimodal GPT-6.1 Sol leads
Gemini 3.7 Flash: 37.3 (#73), GPT-6.1 Sol: 52.7 (#5)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1316 | 1288 |
| Furniture Assembly | 26.7% | 80% |
Multilingual Gemini 3.7 Flash leads
Gemini 3.7 Flash: 57.6 (#7), GPT-6.1 Sol: 54.3 (#46)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1484 | 1438 |
| LMArena Chinese | 1548 | 1477 |
| LMArena Russian | 1516 | 1455 |
| LMArena French | 1505 | — |
| LMArena German | 1498 | — |
| LMArena Japanese | 1512 | — |
| LMArena Korean | 1483 | — |
| LMArena Spanish | 1503 | — |
Instruction Following Too close to call
Gemini 3.7 Flash: 77.7 (#15), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1483 | 1468 |
Long Context Too close to call
Gemini 3.7 Flash: 45.7 (#30), GPT-6.1 Sol: 44.9 (#54)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1492 | 1465 |
Writing & Preference Gemini 3.7 Flash leads
Gemini 3.7 Flash: 71.2 (#20), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | Gemini 3.7 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1486 | 1447 |
| LMArena Creative Writing | 1490 | 1432 |
| LMArena Multi-Turn | 1489 | 1449 |
| EQ-Bench Creative Writing | 1723 | — |
Frequently asked questions
Is Gemini 3.7 Flash better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 2.7× 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, Gemini 3.7 Flash or GPT-6.1 Sol?
Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is Gemini 3.7 Flash or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 56.2 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 3.7 Flash and GPT-6.1 Sol share?
33 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-6.1 Sol has 34.