Gemini 3.7 Flash vs GPT-6 Astra Pro
Gemini 3.7 Flash costs 13.3x less per output token than GPT-6 Astra Pro ($3.75 vs $50.00 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
Gemini 3.7 Flash or GPT-6 Astra Pro: which to pick
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; GPT-6 Astra Pro has none, so the two cannot be ranked on coding.
Pick GPT-6 Astra Pro for a larger context window (1.05M against 1.05M tokens) and work measured by Chess puzzles, where it leads.
- Shared results
- 1
- Gemini 3.7 Flash only
- 113
- GPT-6 Astra Pro only
- 1
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
GPT-6 Astra Pro
GPT-6 Astra Pro takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash $0.0026, GPT-6 Astra Pro $0.035 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-6 Astra Pro not benchmarked.
- Widest category
- Reasoning, 10.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Chess puzzles: Gemini 3.7 Flash 66.0% against GPT-6 Astra Pro 76.0%, 10.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.7 Flash $3.75 against GPT-6 Astra Pro $50.00 per million output tokens, 13.3x apart.
- Context window
- Gemini 3.7 Flash takes 1.05M tokens, GPT-6 Astra Pro 1.05M.
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-6 Astra Pro | Ties |
|---|---|---|---|---|
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index24 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-6 Astra Pro | 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% | Not measured | Only Gemini 3.7 Flash measured |
| 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% | Not measured | Only Gemini 3.7 Flash measured |
| 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 |
| FrontierCode | 43.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierSWE | 20.3% | Not measured | Only Gemini 3.7 Flash measured |
| WeirdML | Not measured | 93.6% | Only GPT-6 Astra Pro measured |
| ALE-Bench | 904.3 | Not measured | Only Gemini 3.7 Flash measured |
| 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 |
| SciCode | 13.8% | 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-6 Astra Pro | 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 index18 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-6 Astra Pro | 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 | 1230 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | 1242 | 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 | 1053 | 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 |
| Remote Labor Index | 5.0% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3.7 Flash | GPT-6 Astra Pro | 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% | 76.0% | GPT-6 Astra Pro |
| 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 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-6 Astra Pro | 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% | Not measured | Only Gemini 3.7 Flash measured |
| 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 index11 boards, none shared
| Benchmark | Gemini 3.7 Flash | GPT-6 Astra Pro | 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 |
| FACTS Benchmark Suite | 71.2% | 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-6 Astra Pro | 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 | 1315 | 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-6 Astra Pro | 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-6 Astra Pro | 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 costs less
Repository review
50K input + 3K output tokens
Gemini 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
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-6 Astra Pro |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | August 13, 2026 | September 4, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.75 | $10.00 |
| Output $/Mtok | $3.75 | $50.00 |
| Coding index | 58.0 | Not benchmarked |
| Independent measurements behind it | 6 | 0 |
| Cost per solved task | $1.78 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.7 Flash better than GPT-6 Astra Pro for coding?
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; GPT-6 Astra Pro has none, so the two cannot be ranked on coding. Pick GPT-6 Astra Pro for a larger context window (1.05M against 1.05M tokens) and work measured by Chess puzzles, where it leads.
Which is cheaper, Gemini 3.7 Flash or GPT-6 Astra Pro?
Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-6 Astra Pro costs $10.00 and $50.00. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Gemini 3.7 Flash or GPT-6 Astra Pro?
GPT-6 Astra Pro, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3.7 Flash vs GPT-6 Astra Pro comparison based on?
1 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-6 Astra Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.