Model comparison
Gemini 3.7 Flash vs GPT-5.5 Pro
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 45× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Last verified . 11 shared benchmarks.
GoogleSummary
- They share 11 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 1 category and GPT-5.5 Pro in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 Pro leads 84.0 to 69.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 36.6% for Gemini 3.7 Flash and 78% for GPT-5.5 Pro.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
- GPT-5.5 Pro accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 3.7 Flash | GPT-5.5 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 59.8 | 64.3 |
| Released | 2026-08-13 | 2026-04-23 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $30 |
| Output $ / M tokens | $3.75 | $180 |
| Results tracked | 44 | 14 |
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Category by category
Coding Not comparable
Gemini 3.7 Flash: 56.2 (#22), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| DeepSWE | 65.5% | — |
| FrontierCode | 43.6% | — |
| LMArena WebDev | 1592 | — |
| FrontierSWE | 20.3% | — |
| SciCode | 59.8% | — |
| LMArena Coding | 1497 | — |
| ALE-Bench | 904.3 | — |
Agentic & Tool Use Not comparable
Gemini 3.7 Flash: 42.1 (#19), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| APEX-Agents | 67.8% | — |
| Remote Labor Index | 5% | — |
| GDP.pdf | 23.8% | — |
Reasoning GPT-5.5 Pro leads
Gemini 3.7 Flash: 70.0 (#15), GPT-5.5 Pro: 73.3 (#10)
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| ARC-AGI-2 | 84.6% | 84.6% |
| ARC-AGI-1 | 95.5% | 96.5% |
| CritPt | 14.3% | 30.6% |
| Chess Puzzles | 47% | 64% |
| DTBench | 96.8% | 96% |
| LMCA | 50.4% | 53.9% |
| Epoch Capabilities Index | 157.27 | 162.07 |
| SimpleBench | — | 76.9% |
| NYT Connections (extended) | 94% | — |
| LMArena Hard Prompts | 1494 | — |
| Mystery Game Puzzles | 37% | — |
Math GPT-5.5 Pro leads
Gemini 3.7 Flash: 69.6 (#23), GPT-5.5 Pro: 84.0 (#10)
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | 87.7% |
| FrontierMath Tier 4 | 36.6% | 78% |
| OTIS Mock AIME 2024-2025 | 97.2% | 100% |
| ProofBench | 58% | — |
| LMArena Math | 1507 | — |
| FrontierMath (Feb 2025 set) | — | 52.4% |
| FrontierMath Tier 4 (v1) | — | 39.6% |
Knowledge Gemini 3.7 Flash leads
Gemini 3.7 Flash: 69.7 (#5), GPT-5.5 Pro: 64.1 (#19)
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| GPQA Diamond | 94.8% | 93.9% |
| SimpleQA Verified | 69.2% | — |
| LMArena Expert | 1508 | — |
Multimodal Not comparable
Gemini 3.7 Flash: 37.3 (#73), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 26.7% | — |
Multilingual Not comparable
Gemini 3.7 Flash: 57.6 (#7), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| LMArena Non-English | 1484 | — |
| LMArena Chinese | 1548 | — |
| LMArena French | 1505 | — |
| LMArena German | 1498 | — |
| LMArena Japanese | 1512 | — |
| LMArena Korean | 1483 | — |
| LMArena Russian | 1516 | — |
| LMArena Spanish | 1503 | — |
Instruction Following Not comparable
Gemini 3.7 Flash: 77.7 (#15), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| LMArena Instruction Following | 1483 | — |
Long Context Not comparable
Gemini 3.7 Flash: 45.7 (#30), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| LMArena Longer Query | 1492 | — |
Writing & Preference Not comparable
Gemini 3.7 Flash: 71.2 (#20), GPT-5.5 Pro: —
| Benchmark | Gemini 3.7 Flash | GPT-5.5 Pro |
|---|---|---|
| LMArena Text | 1486 | — |
| LMArena Creative Writing | 1490 | — |
| EQ-Bench Creative Writing | 1723 | — |
| LMArena Multi-Turn | 1489 | — |
Frequently asked questions
Is Gemini 3.7 Flash better than GPT-5.5 Pro?
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 45× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 3.7 Flash or GPT-5.5 Pro?
Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.5 Pro lists at $30 and $180.
Which has the bigger context window?
GPT-5.5 Pro does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 3.7 Flash and GPT-5.5 Pro share?
11 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5.5 Pro has 14.