Model comparison
Gemini 3.7 Flash vs GPT-5.1-Codex-mini
Gemini 3.7 Flash has enough public results to be ranked (#14); GPT-5.1-Codex-mini does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. Gemini 3.7 Flash scores higher in 2 categories and GPT-5.1-Codex-mini in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Gemini 3.7 Flash leads 56.2 to 31.6.
- GPT-5.1-Codex-mini is cheaper at $0.25 / $2 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.7 Flash.
- Gemini 3.7 Flash accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 3.7 Flash | GPT-5.1-Codex-mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 59.8 | 37.3 |
| Released | 2026-08-13 | 2025-11-12 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $0.25 |
| Output $ / M tokens | $3.75 | $2 |
| Results tracked | 44 | 2 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 3.7 Flash leads
Gemini 3.7 Flash: 56.2 (#22), GPT-5.1-Codex-mini: 31.6
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena WebDev | 1592 | 1244 |
| DeepSWE | 65.5% | — |
| FrontierCode | 43.6% | — |
| FrontierSWE | 20.3% | — |
| SciCode | 59.8% | — |
| LMArena Coding | 1497 | — |
| ALE-Bench | 904.3 | — |
Agentic & Tool Use Gemini 3.7 Flash leads
Gemini 3.7 Flash: 42.1 (#19), GPT-5.1-Codex-mini: 38.5
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| Terminal-Bench | — | 61.6% |
| APEX-Agents | 67.8% | — |
| Remote Labor Index | 5% | — |
| GDP.pdf | 23.8% | — |
Reasoning Not comparable
Gemini 3.7 Flash: 70.0 (#15), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| ARC-AGI-2 | 84.6% | — |
| NYT Connections (extended) | 94% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | 47% | — |
| LMArena Hard Prompts | 1494 | — |
| Mystery Game Puzzles | 37% | — |
| DTBench | 96.8% | — |
| LMCA | 50.4% | — |
| Epoch Capabilities Index | 157.27 | — |
Math Not comparable
Gemini 3.7 Flash: 69.6 (#23), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | — |
| FrontierMath Tier 4 | 36.6% | — |
| OTIS Mock AIME 2024-2025 | 97.2% | — |
| ProofBench | 58% | — |
| LMArena Math | 1507 | — |
Knowledge Not comparable
Gemini 3.7 Flash: 69.7 (#5), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| GPQA Diamond | 94.8% | — |
| SimpleQA Verified | 69.2% | — |
| LMArena Expert | 1508 | — |
Multimodal Not comparable
Gemini 3.7 Flash: 37.3 (#73), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 26.7% | — |
Multilingual Not comparable
Gemini 3.7 Flash: 57.6 (#7), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| 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-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Instruction Following | 1483 | — |
Long Context Not comparable
Gemini 3.7 Flash: 45.7 (#30), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Longer Query | 1492 | — |
Writing & Preference Not comparable
Gemini 3.7 Flash: 71.2 (#20), GPT-5.1-Codex-mini: —
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-mini |
|---|---|---|
| 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-5.1-Codex-mini?
Gemini 3.7 Flash has enough public results to be ranked (#14); GPT-5.1-Codex-mini does not yet, so treat this comparison as directional.
Which is cheaper, Gemini 3.7 Flash or GPT-5.1-Codex-mini?
GPT-5.1-Codex-mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Gemini 3.7 Flash lists at $0.75 and $3.75.
Is Gemini 3.7 Flash or GPT-5.1-Codex-mini better for coding?
Gemini 3.7 Flash scores higher on coding benchmarks: 56.2 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.7 Flash does, with 1.05M tokens against 400K.
How many benchmarks do Gemini 3.7 Flash and GPT-5.1-Codex-mini share?
1 benchmark has published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5.1-Codex-mini has 2.