Gemini 3.7 Flash vs GPT-5.1-Codex-Max
Updated October 21, 2026. 4 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 4 shared
Decision reading
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding.
GPT-5.1-Codex-Max has the edge where the benchmark that matters is ALE-Bench, where it leads.
Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BGPT-5.1-Codex-MaxOpenAINot benchmarked1 independent benchmarkNo cost per solved task
- Shared results
- 4
- Gemini 3.7 Flash only
- 108
- GPT-5.1-Codex-Max only
- 2
- Like-for-like categories
- 2 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Gemini 3.7 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemini 3.7 Flash has a AA Intelligence Index result, 39.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 3.7 Flash has a Design Arena: websites result, 1304.
Directional only
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash $0.0026, GPT-5.1-Codex-Max $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- Gemini 3.7 Flash 58.0 from 6 benchmarks, GPT-5.1-Codex-Max not benchmarked.
- Widest category
- Math, 49.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: Gemini 3.7 Flash 58.0% against GPT-5.1-Codex-Max 9.0%, 49.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.7 Flash $3.75 against GPT-5.1-Codex-Max $10.00 per million output tokens, 2.7x apart.
- Context window
- Gemini 3.7 Flash takes 1.05M tokens, GPT-5.1-Codex-Max 400K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemini 3.7 Flash | Bars | GPT-5.1-Codex-Max | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Math | 1 | 0 | ||
| All shared boards | 3 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| LiveBench coding | 80.5% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev | 1591 | Not measured | Only Gemini 3.7 Flash measured |
| AA Coding Index | 71.5 | Not measured | Only Gemini 3.7 Flash measured |
| LiveCodeBench (Vals AI) | 88.7% | 83.6% | Gemini 3.7 Flash |
| SWE-bench Verified (Vals AI) | 80.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | 12.1% | Not measured | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | 70.4% | 22.2% | Gemini 3.7 Flash |
| Code migration (Vals AI) | 34.8% | Not measured | Only Gemini 3.7 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | Not measured | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | 65.9% | Not measured | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | 43.8% | Not measured | Only Gemini 3.7 Flash measured |
| SciCode | 59.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench | Not measured | 60.4% | Only GPT-5.1-Codex-Max measured |
| FrontierCode | 43.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierSWE | 20.3% | Not measured | Only Gemini 3.7 Flash measured |
| ALE-Bench | 904.3 | 1228.3 | GPT-5.1-Codex-Max |
| LMArena Text: coding | 1499 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: software and IT | 1498 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev: React | 1587 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev: HTML | 1593 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev: from an image | 1599 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.6 | Not measured | Only Gemini 3.7 Flash measured |
| Epoch Capabilities Index | 158.0 | Not measured | Only Gemini 3.7 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1223 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | 1208 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | 1232 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | 1248 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | 1264 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | 1235 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | 1022 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench research | 76.5% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench browser | 56.0% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | 28.3% | Not measured | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | 4.6% | Not measured | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | 59.0% | Not measured | Only Gemini 3.7 Flash measured |
| Tax Agent Bench (Vals AI) | 22.8% | Not measured | Only Gemini 3.7 Flash measured |
| Legal Research Bench (Vals AI) | 34.6% | Not measured | Only Gemini 3.7 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 71.3% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench-Science (Vals AI) | 7.1% | Not measured | Only Gemini 3.7 Flash measured |
| APEX-Agents | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| METR time horizons | Not measured | 70.8% | Only GPT-5.1-Codex-Max measured |
| Remote Labor Index | 5.0% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| GPQA Diamond | 93.9% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | 87.8% | Not measured | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | 89.0% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 94.5% | Not measured | Only Gemini 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Epoch AI run) | 94.8% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI | 95.5% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | 84.6% | Not measured | Only Gemini 3.7 Flash measured |
| Chess puzzles | 66.0% | Not measured | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | 37.0% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | 1495 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: expert | 1512 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts in English | 1487 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: diagrams | 1329 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | 1320 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | 97.2% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | 71.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | 36.6% | Not measured | Only Gemini 3.7 Flash measured |
| ProofBench | 58.0% | 9.0% | Gemini 3.7 Flash |
| LMArena Text: math | 1511 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: mathematical work | 1502 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| MMLU Pro | 90.1% | Not measured | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | 87.3% | Not measured | Only Gemini 3.7 Flash measured |
| TaxEval (Vals AI) | 74.7% | Not measured | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | 66.7% | Not measured | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | 53.4% | Not measured | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | 69.2% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: science | 1511 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: medicine and healthcare | 1494 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: legal and government | 1496 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: business and finance | 1479 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1304 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: UI components | 1299 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: game dev | 1318 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: data viz | 1314 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: 3D | 1308 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: all code categories | 1308 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: SVG | 1283 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: ASCII art | 1276 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench design | 73.2% | Not measured | Only Gemini 3.7 Flash measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| LiveBench data analysis | 68.0% | Not measured | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | 49.2% | Not measured | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | 83.9% | Not measured | Only Gemini 3.7 Flash measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only Gemini 3.7 Flash measured |
| DTBench | 96.8% | Not measured | Only Gemini 3.7 Flash measured |
| LMCA | 50.4% | Not measured | Only Gemini 3.7 Flash measured |
| Furniture assembly | 26.7% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text | 1489 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: instruction following | 1484 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: creative writing | 1488 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision | 1314 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: English | 1483 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: non-English | 1487 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Chinese | 1552 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: German | 1506 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Japanese | 1511 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | 1481 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: French | 1500 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Spanish | 1495 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Russian | 1515 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Polish | 1503 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: multi-turn | 1485 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: longer queries | 1492 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: writing and language | 1491 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: entertainment and media | 1477 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: English | 1309 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | 1394 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | 1322 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | 1299 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | 1312 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Gemini 3.7 Flash$0.0026Fits in one request
GPT-5.1-Codex-Max$0.0063Fits in one request
Gemini 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 3.7 Flash$0.049Fits in one request
GPT-5.1-Codex-Max$0.092Fits in one request
Gemini 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 3.7 Flash$0.188Fits in one request
GPT-5.1-Codex-Max$0.350Fits in one request
Gemini 3.7 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Gemini 3.7 Flash | OpenAI GPT-5.1-Codex-Max |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | August 13, 2026 | December 4, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.75 | $1.25 |
| Output $/Mtok | $3.75 | $10.00 |
| Coding index | 58.0 | Not benchmarked |
| Independent measurements behind it | 6 | 1 |
| Cost per solved task | $1.78 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.7 Flash better than GPT-5.1-Codex-Max for coding?
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding. GPT-5.1-Codex-Max has the edge where the benchmark that matters is ALE-Bench, where it leads.
Which is cheaper, Gemini 3.7 Flash or GPT-5.1-Codex-Max?
Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.1-Codex-Max costs $1.25 and $10.00. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Gemini 3.7 Flash or GPT-5.1-Codex-Max?
Gemini 3.7 Flash, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 3.7 Flash vs GPT-5.1-Codex-Max comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and GPT-5.1-Codex-Max's on 1. Where only one model has a result, the page says so instead of naming a winner.