Gemini 3.5 Flash vs GPT-6 Astra
Updated October 21, 2026. 88 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-6 Astra for coding: it scores 88.7 on the Vibe Coding Index against 42.8 for Gemini 3.5 Flash.
Pick Gemini 3.5 Flash when output tokens cost 5.6x less, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 88
- Gemini 3.5 Flash only
- 22
- GPT-6 Astra only
- 31
- Like-for-like categories
- 8 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, four public coding benchmarks
GPT-6 Astra
GPT-6 Astra scores 88.7 against 42.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6 Astra
GPT-6 Astra leads, 52.7 against 33.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-6 Astra has a AA Agentic Index result, 51.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
GPT-6 Astra
GPT-6 Astra leads, 1337 against 1268.
Same board, both measured
General
Vals Index
No call
Only GPT-6 Astra has a Vals Index result, 65.0%.
Directional only
Long documents
Listed context window
GPT-6 Astra
GPT-6 Astra takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.5 Flash
Gemini 3.5 Flash $0.0060, GPT-6 Astra $0.035 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash 42.8 from 1 benchmark, GPT-6 Astra 88.7 from 2 benchmarks.
- Widest category
- Math, 30.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- EBR-bench: Gemini 3.5 Flash 4.8% against GPT-6 Astra 76.2%, 71.4 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash $9.00 against GPT-6 Astra $50.00 per million output tokens, 5.6x apart.
- Context window
- Gemini 3.5 Flash takes 1.05M tokens, GPT-6 Astra 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 3.5 Flash | Bars | GPT-6 Astra | Ties |
|---|---|---|---|---|
| Coding | 2 | 12 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 2 | 10 | ||
| Reasoning | 4 | 9 | ||
| Math | 2 | 4 | ||
| Knowledge | 5 | 1 | ||
| Web design | 0 | 8 | ||
| General | 23 | 4 | ||
| All shared boards | 38 | 50 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index212
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 93.7% | Only GPT-6 Astra measured |
| LMArena WebDev | 1499 | 1774 | GPT-6 Astra |
| AA Coding Index | Not measured | 76.9 | Only GPT-6 Astra measured |
| LiveCodeBench (Vals AI) | 87.6% | Not measured | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | 59.6% | GPT-6 Astra |
| Vibe Code Bench (Vals AI) | 48.7% | 89.6% | GPT-6 Astra |
| Code migration (Vals AI) | 26.8% | 67.7% | GPT-6 Astra |
| ProgramBench (Vals AI) | 0.0% | 5.5% | GPT-6 Astra |
| IOI (Vals AI) | Not measured | 100.0% | Only GPT-6 Astra measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | 87.3% | GPT-6 Astra |
| SWE-bench Multimodal (Vals AI) | Not measured | 43.3% | Only GPT-6 Astra measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 27.6% | Only GPT-6 Astra measured |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| CyberBench (Vals AI) | Not measured | 41.1% | Only GPT-6 Astra measured |
| SciCode | 53.9% | 56.5% | GPT-6 Astra |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierCode | Not measured | 53.3% | Only GPT-6 Astra measured |
| FrontierSWE | Not measured | 65.5% | Only GPT-6 Astra measured |
| GSO-Bench | Not measured | 79.4% | Only GPT-6 Astra measured |
| WeirdML | 62.6% | 93.3% | GPT-6 Astra |
| MirrorCode | Not measured | 46.7% | Only GPT-6 Astra measured |
| ALE-Bench | 911.0 | 2951.3 | GPT-6 Astra |
| LMArena Text: coding | 1493 | 1489 | Gemini 3.5 Flash |
| LMArena Text: software and IT | 1494 | 1474 | Gemini 3.5 Flash |
| LMArena WebDev: React | 1495 | 1798 | GPT-6 Astra |
| LMArena WebDev: HTML | 1522 | 1775 | GPT-6 Astra |
| LMArena WebDev: from an image | 1504 | 1726 | GPT-6 Astra |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.6 | 52.7 | GPT-6 Astra |
| Epoch Capabilities Index | 154.9 | 168.8 | GPT-6 Astra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index210
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 51.0 | Only GPT-6 Astra measured |
| Design Arena: agents building web apps | 1202 | 1372 | GPT-6 Astra |
| Design Arena: agents building full-stack apps | 1197 | 1357 | GPT-6 Astra |
| Design Arena: agents building mobile apps | 1175 | 1312 | GPT-6 Astra |
| Design Arena: agents building Android apps | 1190 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | 1098 | 1348 | GPT-6 Astra |
| Design Arena: agents building games | 1180 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | 1142 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | 1178 | 1245 | GPT-6 Astra |
| Design Arena: spreadsheets | Not measured | 1380 | Only GPT-6 Astra measured |
| LiveBench research | Not measured | 85.2% | Only GPT-6 Astra measured |
| LiveBench browser | Not measured | 84.0% | Only GPT-6 Astra measured |
| LiveBench long agentic | Not measured | 82.4% | Only GPT-6 Astra measured |
| SREBench (Vals AI) | Not measured | 56.9% | Only GPT-6 Astra measured |
| Finance Agent (Vals AI) | 57.9% | 53.5% | Gemini 3.5 Flash |
| Tax Agent Bench (Vals AI) | 21.6% | 20.7% | Gemini 3.5 Flash |
| Legal Research Bench (Vals AI) | 30.8% | 39.4% | GPT-6 Astra |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 7.1% | Only GPT-6 Astra measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | 71.7% | GPT-6 Astra |
| BioMysteryBench (Vals AI) | Not measured | 79.3% | Only GPT-6 Astra measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | 62.9% | GPT-6 Astra |
| Vals Science Index | Not measured | 65.1% | Only GPT-6 Astra measured |
| Time Horizon Index (Vals AI) | Not measured | 90.5% | Only GPT-6 Astra measured |
| CUA-bench (Vals AI) | Not measured | 19.2% | Only GPT-6 Astra measured |
| Robo-bench (Vals AI) | Not measured | 23.3% | Only GPT-6 Astra measured |
| τ²-Bench Telecom | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| APEX-Agents | 27.5% | 64.7% | GPT-6 Astra |
| Remote Labor Index | Not measured | 20.8% | Only GPT-6 Astra measured |
| BALROG | Not measured | 68.3% | Only GPT-6 Astra measured |
| SpireClimb | Not measured | 25.7% | Only GPT-6 Astra measured |
| Vending-Bench 2 | $5,396 | $15,515 | GPT-6 Astra |
| Neither model has a result on the other 8 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index49
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only Gemini 3.5 Flash measured |
| LiveBench reasoning | Not measured | 92.7% | Only GPT-6 Astra measured |
| MysteryMechanism (Vals AI) | Not measured | 53.1% | Only GPT-6 Astra measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | 96.3% | GPT-6 Astra |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 54.7% | GPT-6 Astra |
| GPQA Diamond (Epoch AI run) | 92.8% | 95.8% | GPT-6 Astra |
| ARC-AGI | 92.5% | 98.5% | GPT-6 Astra |
| ARC-AGI-2 | 72.1% | 95.0% | GPT-6 Astra |
| SimpleBench | 76.7% | Not measured | Only Gemini 3.5 Flash measured |
| Chess puzzles | 45.0% | 74.0% | GPT-6 Astra |
| Mystery game puzzles | 32.0% | 84.0% | GPT-6 Astra |
| EBR-bench | 4.8% | 76.2% | GPT-6 Astra |
| LMArena Text: hard prompts | 1488 | 1463 | Gemini 3.5 Flash |
| LMArena Text: expert | 1495 | 1489 | Gemini 3.5 Flash |
| LMArena Text: hard prompts in English | 1483 | 1464 | Gemini 3.5 Flash |
| LMArena Vision: diagrams | 1323 | 1297 | Gemini 3.5 Flash |
| LMArena Vision: homework | 1330 | 1337 | GPT-6 Astra |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | 100.0% | GPT-6 Astra |
| FrontierMath, tiers 1 to 3 | 62.8% | 93.7% | GPT-6 Astra |
| FrontierMath, tier 4 | 26.8% | 97.6% | GPT-6 Astra |
| ProofBench | 31.0% | 99.0% | GPT-6 Astra |
| LMArena Text: math | 1504 | 1465 | Gemini 3.5 Flash |
| LMArena Text: mathematical work | 1495 | 1484 | Gemini 3.5 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | Not measured | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | 64.7% | Not measured | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | 74.4% | Not measured | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | 55.8% | 48.5% | Gemini 3.5 Flash |
| SimpleQA Verified | 66.2% | 75.6% | GPT-6 Astra |
| LMArena Text: science | 1495 | 1451 | Gemini 3.5 Flash |
| LMArena Text: medicine and healthcare | 1483 | 1425 | Gemini 3.5 Flash |
| LMArena Text: legal and government | 1488 | 1462 | Gemini 3.5 Flash |
| LMArena Text: business and finance | 1467 | 1439 | Gemini 3.5 Flash |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | 1337 | GPT-6 Astra |
| Design Arena: UI components | 1272 | 1394 | GPT-6 Astra |
| Design Arena: game dev | 1263 | 1474 | GPT-6 Astra |
| Design Arena: data viz | 1236 | 1335 | GPT-6 Astra |
| Design Arena: 3D | 1244 | 1501 | GPT-6 Astra |
| Design Arena: all code categories | 1266 | 1379 | GPT-6 Astra |
| Design Arena: SVG | 1254 | 1431 | GPT-6 Astra |
| Design Arena: ASCII art | 1253 | 1359 | GPT-6 Astra |
| LiveBench design | Not measured | 82.0% | Only GPT-6 Astra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index234
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | Leader |
|---|---|---|---|
| Vals Index | Not measured | 65.0% | Only GPT-6 Astra measured |
| LiveBench data analysis | Not measured | 83.0% | Only GPT-6 Astra measured |
| Public Benefits Bench (Vals AI) | 59.5% | Not measured | Only Gemini 3.5 Flash measured |
| SAGE (Vals AI) | 49.9% | 46.4% | Gemini 3.5 Flash |
| MedScribe (Vals AI) | 76.6% | 87.9% | GPT-6 Astra |
| Vals Multimodal Index | 62.9% | Not measured | Only Gemini 3.5 Flash measured |
| IFBench | 76.3% | Not measured | Only Gemini 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 74.3% | 80.7% | GPT-6 Astra |
| DTBench | 94.7% | 97.3% | GPT-6 Astra |
| LMCA | 47.1% | 64.4% | GPT-6 Astra |
| Surface Evolver Bench | 58.1% | Not measured | Only Gemini 3.5 Flash measured |
| Furniture assembly | Not measured | 80.0% | Only GPT-6 Astra measured |
| LMArena Text | 1482 | 1441 | Gemini 3.5 Flash |
| LMArena Text: instruction following | 1467 | 1455 | Gemini 3.5 Flash |
| LMArena Text: creative writing | 1470 | 1420 | Gemini 3.5 Flash |
| LMArena Vision | 1308 | 1280 | Gemini 3.5 Flash |
| LMArena Text: English | 1481 | 1447 | Gemini 3.5 Flash |
| LMArena Text: non-English | 1475 | 1432 | Gemini 3.5 Flash |
| LMArena Text: Chinese | 1527 | 1489 | Gemini 3.5 Flash |
| LMArena Text: German | 1494 | 1459 | Gemini 3.5 Flash |
| LMArena Text: Japanese | 1486 | 1405 | Gemini 3.5 Flash |
| LMArena Text: Korean | 1448 | 1428 | Gemini 3.5 Flash |
| LMArena Text: French | 1490 | 1432 | Gemini 3.5 Flash |
| LMArena Text: Spanish | 1480 | 1422 | Gemini 3.5 Flash |
| LMArena Text: Russian | 1493 | 1438 | Gemini 3.5 Flash |
| LMArena Text: Polish | 1516 | 1422 | Gemini 3.5 Flash |
| LMArena Text: multi-turn | 1481 | 1447 | Gemini 3.5 Flash |
| LMArena Text: longer queries | 1483 | 1460 | Gemini 3.5 Flash |
| LMArena Text: writing and language | 1478 | 1437 | Gemini 3.5 Flash |
| LMArena Text: entertainment and media | 1459 | 1427 | Gemini 3.5 Flash |
| LMArena Vision: English | 1305 | 1280 | Gemini 3.5 Flash |
| LMArena Vision: Chinese | 1377 | 1361 | Gemini 3.5 Flash |
| LMArena Vision: reading text | 1317 | 1292 | Gemini 3.5 Flash |
| LMArena Vision: humor | 1321 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | 1301 | 1286 | Gemini 3.5 Flash |
| LMArena Document | 1463 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | GPT-6 Astra | 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 3.5 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 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 3.5 Flash | OpenAI GPT-6 Astra |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | May 19, 2026 | September 4, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.50 | $10.00 |
| Output $/Mtok | $9.00 | $50.00 |
| Coding index | 42.8 | 88.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than GPT-6 Astra for coding?
Pick GPT-6 Astra for coding: it scores 88.7 on the Vibe Coding Index against 42.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash when output tokens cost 5.6x less, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Gemini 3.5 Flash or GPT-6 Astra?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GPT-6 Astra costs $10.00 and $50.00. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, Gemini 3.5 Flash or GPT-6 Astra?
GPT-6 Astra, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3.5 Flash vs GPT-6 Astra comparison based on?
88 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 1 independent benchmark and GPT-6 Astra's on 2. Where only one model has a result, the page says so instead of naming a winner.