Model comparison
Gemini 3.5 Flash vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 54.2 on the Noometry Index.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. Gemini 3.5 Flash scores higher in 3 categories and GPT-6.1 Sol in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 60.7.
- The biggest single-benchmark swing is FrontierMath Tier 4: 26.8% for Gemini 3.5 Flash and 100% for GPT-6.1 Sol.
- Gemini 3.5 Flash is cheaper at $1.50 / $9 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 3.5 Flash | GPT-6.1 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 54.2 | 65.6 |
| Released | 2026-05-19 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $1.50 | $2 |
| Output $ / M tokens | $9 | $10 |
| Results tracked | 54 | 34 |
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Category by category
Coding GPT-6.1 Sol leads
Gemini 3.5 Flash: 49.4 (#49), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| DeepSWE | 37.4% | 75.2% |
| LMArena WebDev | 1499 | 1755 |
| SciCode | 53.1% | 55.8% |
| LMArena Coding | 1492 | 1487 |
| SWE-bench Verified | 79.3% | — |
| FrontierCode | — | 50.2% |
| WeirdML | 62.6% | — |
| ALE-Bench | 911.02 | — |
Agentic & Tool Use GPT-6.1 Sol leads
Gemini 3.5 Flash: 24.7 (#114), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | 27.5% | 60% |
| GDP.pdf | 14% | 32% |
| GBAEval | 6.7% | — |
| Vending-Bench 2 | 5,396 | — |
Reasoning GPT-6.1 Sol leads
Gemini 3.5 Flash: 62.8 (#18), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| ARC-AGI-2 | 72.1% | 94.2% |
| NYT Connections (extended) | 92.6% | 95.5% |
| ARC-AGI-1 | 92.5% | 98.5% |
| CritPt | 13.1% | 31.7% |
| Chess Puzzles | 50% | 61% |
| EBR-Bench | 4.8% | 54.3% |
| LMArena Hard Prompts | 1488 | 1466 |
| Mystery Game Puzzles | 32% | 80% |
| Epoch Capabilities Index | 154.46 | 166.09 |
| SimpleBench | 76.7% | — |
| EnigmaEval | 25.4% | — |
| DTBench | 94.7% | — |
| LMCA | 47.1% | — |
| Surface Evolver Bench | 58.1% | — |
| ForecastBench | 59 | — |
Math GPT-6.1 Sol leads
Gemini 3.5 Flash: 60.7 (#36), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 62.8% | 93.7% |
| FrontierMath Tier 4 | 26.8% | 100% |
| OTIS Mock AIME 2024-2025 | 95.6% | 100% |
| ProofBench | 31% | 99% |
| LMArena Math | 1504 | 1464 |
| MathArena Final-Answer Competitions | 76.3% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge GPT-6.1 Sol leads
Gemini 3.5 Flash: 66.3 (#11), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 92.8% | 95.4% |
| SimpleQA Verified | 66.2% | 73.9% |
| LMArena Expert | 1495 | 1502 |
Multimodal GPT-6.1 Sol leads
Gemini 3.5 Flash: 45.7 (#15), GPT-6.1 Sol: 52.7 (#5)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1310 | 1288 |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | — | 80% |
| LMArena Document | 1463 | — |
Multilingual Gemini 3.5 Flash leads
Gemini 3.5 Flash: 57.0 (#13), GPT-6.1 Sol: 54.3 (#46)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1476 | 1438 |
| LMArena Chinese | 1526 | 1477 |
| LMArena Russian | 1493 | 1455 |
| LMArena French | 1490 | — |
| LMArena German | 1492 | — |
| LMArena Japanese | 1486 | — |
| LMArena Korean | 1451 | — |
| LMArena Spanish | 1480 | — |
Instruction Following Too close to call
Gemini 3.5 Flash: 77.0 (#30), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1467 | 1468 |
Long Context Too close to call
Gemini 3.5 Flash: 45.4 (#38), GPT-6.1 Sol: 44.9 (#54)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1482 | 1465 |
Writing & Preference Gemini 3.5 Flash leads
Gemini 3.5 Flash: 65.5 (#47), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1482 | 1447 |
| LMArena Creative Writing | 1470 | 1432 |
| LMArena Multi-Turn | 1481 | 1449 |
| EQ-Bench 4 | 1087 | — |
Frequently asked questions
Is Gemini 3.5 Flash better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 54.2 on the Noometry Index.
Which is cheaper, Gemini 3.5 Flash or GPT-6.1 Sol?
Gemini 3.5 Flash is cheaper. It lists at $1.50 per million input tokens and $9 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is Gemini 3.5 Flash or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 49.4 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 3.5 Flash and GPT-6.1 Sol share?
32 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and GPT-6.1 Sol has 34.