Model comparison
Gemini 1.5 Flash (May 2024) vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 33.2 on the Noometry Index.
Last verified . 16 shared benchmarks.
GoogleSummary
- They share 16 benchmarks with published results for both. Gemini 1.5 Flash (May 2024) scores higher in 0 categories and GPT-6.1 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 22.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.3% for Gemini 1.5 Flash (May 2024) and 100% for GPT-6.1 Sol.
Side by side
| Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 33.2 | 65.6 |
| Released | 2024-05-14 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $10 |
| Results tracked | 42 | 34 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 34.4 (#236), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Coding | 1261 | 1487 |
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |
| WeirdML | 24.9% | — |
| BigCodeBench Instruct | 43.5% | — |
| BigCodeBench Complete | 55.1% | — |
| HumanEval+ | 75.6% | — |
| MBPP+ | 67.5% | — |
Agentic & Tool Use GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 26.6 (#102), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| BALROG | 14.6% | — |
| GDP.pdf | — | 32% |
Reasoning GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 21.7 (#215), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Hard Prompts | 1257 | 1466 |
| Epoch Capabilities Index | 129.36 | 166.09 |
| ARC-AGI-2 | — | 94.2% |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| Chess Puzzles | — | 61% |
| EBR-Bench | — | 54.3% |
| Mystery Game Puzzles | — | 80% |
| DTBench | 53.8% | — |
| ForecastBench | 53.9 | — |
| PIQA | 87.5% | — |
Math GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 22.1 (#281), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.3% | 100% |
| LMArena Math | 1269 | 1464 |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 100% |
| ProofBench | — | 99% |
| Omni-MATH | 30.4% | — |
| MATH Level 5 | 61.9% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
| GSM8K | 82.4% | — |
Knowledge GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 26.2 (#260), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 47.3% | 95.4% |
| LMArena Expert | 1233 | 1502 |
| SimpleQA Verified | — | 73.9% |
| MMLU-Pro | 67.8% | — |
| GPQA (HELM) | 43.7% | — |
| BoolQ | 85.8% | — |
| MMLU | 77.9% | — |
Multimodal GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 36.0 (#81), GPT-6.1 Sol: 52.7 (#5)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1141 | 1288 |
| Video-MME | 70.3% | — |
| GeoBench | 76% | — |
| Furniture Assembly | — | 80% |
Multilingual GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 42.9 (#189), GPT-6.1 Sol: 54.3 (#46)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1278 | 1438 |
| LMArena Chinese | 1295 | 1477 |
| LMArena Russian | 1288 | 1455 |
| LMArena French | 1258 | — |
| LMArena German | 1262 | — |
| LMArena Japanese | 1252 | — |
| LMArena Korean | 1221 | — |
| LMArena Spanish | 1243 | — |
Instruction Following GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 66.8 (#205), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1258 | 1468 |
| IFEval | 83.1% | — |
Long Context GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 39.0 (#187), GPT-6.1 Sol: 44.9 (#54)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1284 | 1465 |
Writing & Preference GPT-6.1 Sol leads
Gemini 1.5 Flash (May 2024): 48.7 (#196), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1287 | 1447 |
| LMArena Creative Writing | 1285 | 1432 |
| LMArena Multi-Turn | 1253 | 1449 |
| WildBench | 79.2% | — |
Frequently asked questions
Is Gemini 1.5 Flash (May 2024) better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 33.2 on the Noometry Index.
Is Gemini 1.5 Flash (May 2024) or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 34.4 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Flash (May 2024) and GPT-6.1 Sol share?
16 benchmarks have published results for both models. Gemini 1.5 Flash (May 2024) has 42 scored results on Noometry and GPT-6.1 Sol has 34.