Gemini 2.5 Flash vs GPT-5.6 Sol
Updated October 21, 2026. 61 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 61 shared
Decision reading
Pick GPT-5.6 Sol for coding: it scores 76.7 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash.
Pick Gemini 2.5 Flash when output tokens cost 8.0x less, or when a solved task costs $0.466 against $1.20.
Model AGemini 2.5 FlashGoogle28.7/1001 independent benchmark$0.466 per solved taskModel BGPT-5.6 SolOpenAI76.7/1002 independent benchmarks$1.20 per solved task
- Shared results
- 61
- Gemini 2.5 Flash only
- 8
- GPT-5.6 Sol only
- 75
- 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-5.6 Sol
GPT-5.6 Sol scores 76.7 against 28.7.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 15.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Sol has a AA Agentic Index result, 50.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Sol
GPT-5.6 Sol leads, 1321 against 1074.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Sol
GPT-5.6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash
Gemini 2.5 Flash $0.0015, GPT-5.6 Sol $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 2.5 Flash
Gemini 2.5 Flash $0.466, GPT-5.6 Sol $1.20.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Flash 28.7 from 1 benchmark, GPT-5.6 Sol 76.7 from 2 benchmarks.
- Widest category
- Agentic work, 45.6 points apart on average over 3 shared benchmarks.
- Widest single gap
- ARC-AGI-2: Gemini 2.5 Flash 2.5% against GPT-5.6 Sol 92.5%, 90.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against GPT-5.6 Sol $20.00 per million output tokens, 8.0x apart.
- Context window
- Gemini 2.5 Flash takes 1.05M tokens, GPT-5.6 Sol 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 2.5 Flash | Bars | GPT-5.6 Sol | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 10 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 5 | ||
| Web design | 0 | 7 | ||
| General | 0 | 29 | ||
| All shared boards | 0 | 61 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | Not measured | Only Gemini 2.5 Flash measured |
| LiveBench coding | Not measured | 89.7% | Only GPT-5.6 Sol measured |
| LMArena WebDev | Not measured | 1616 | Only GPT-5.6 Sol measured |
| AA Coding Index | Not measured | 77.4 | Only GPT-5.6 Sol measured |
| LiveCodeBench (Vals AI) | Not measured | 82.6% | Only GPT-5.6 Sol measured |
| SWE-bench Verified (Vals AI) | Not measured | 96.2% | Only GPT-5.6 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 37.9% | Only GPT-5.6 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 80.5% | Only GPT-5.6 Sol measured |
| Code migration (Vals AI) | Not measured | 52.9% | Only GPT-5.6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 1.5% | Only GPT-5.6 Sol measured |
| IOI (Vals AI) | Not measured | 91.2% | Only GPT-5.6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 85.8% | Only GPT-5.6 Sol measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| SkillsBench (Vals AI) | Not measured | 54.1% | Only GPT-5.6 Sol measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-5.6 Sol measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | Not measured | Only Gemini 2.5 Flash measured |
| SciCode | Not measured | 57.8% | Only GPT-5.6 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 65.9% | GPT-5.6 Sol |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| FrontierCode | Not measured | 47.5% | Only GPT-5.6 Sol measured |
| FrontierSWE | Not measured | 32.2% | Only GPT-5.6 Sol measured |
| GSO-Bench | Not measured | 76.5% | Only GPT-5.6 Sol measured |
| WeirdML | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| MirrorCode | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| ALE-Bench | Not measured | 2176.9 | Only GPT-5.6 Sol measured |
| LMArena Text: coding | 1423 | 1496 | GPT-5.6 Sol |
| LMArena Text: software and IT | 1425 | 1489 | GPT-5.6 Sol |
| LMArena WebDev: React | Not measured | 1620 | Only GPT-5.6 Sol measured |
| LMArena WebDev: HTML | Not measured | 1618 | Only GPT-5.6 Sol measured |
| LMArena WebDev: from an image | Not measured | 1609 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 8 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | 47.0 | GPT-5.6 Sol |
| Epoch Capabilities Index | 142.9 | 162.8 | GPT-5.6 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.2 | Only GPT-5.6 Sol measured |
| Design Arena: agents building web apps | Not measured | 1245 | Only GPT-5.6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1249 | Only GPT-5.6 Sol measured |
| Design Arena: agents building Android apps | Not measured | 1246 | Only GPT-5.6 Sol measured |
| Design Arena: agents building Godot games | Not measured | 1260 | Only GPT-5.6 Sol measured |
| Design Arena: agents building games | Not measured | 1267 | Only GPT-5.6 Sol measured |
| Design Arena: HTML slides | Not measured | 1286 | Only GPT-5.6 Sol measured |
| Design Arena: PowerPoint slides | Not measured | 1240 | Only GPT-5.6 Sol measured |
| LiveBench research | Not measured | 54.5% | Only GPT-5.6 Sol measured |
| LiveBench browser | Not measured | 88.0% | Only GPT-5.6 Sol measured |
| LiveBench long agentic | Not measured | 48.5% | Only GPT-5.6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-5.6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 53.8% | Only GPT-5.6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 31.1% | Only GPT-5.6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 48.1% | Only GPT-5.6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 72.3% | Only GPT-5.6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 71.1% | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| Vals Science Index | Not measured | 41.5% | Only GPT-5.6 Sol measured |
| Time Horizon Index (Vals AI) | Not measured | 23.8% | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | Not measured | 8.3% | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | 31.6% | 85.1% | GPT-5.6 Sol |
| OSWorld 2.0 | Not measured | 27.3% | Only GPT-5.6 Sol measured |
| BALROG | 33.5% | 60.0% | GPT-5.6 Sol |
| PostTrainBench | Not measured | 36.2% | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | $549 | $9,619 | GPT-5.6 Sol |
| LMArena Search | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 95.2% | Only GPT-5.6 Sol measured |
| LiveBench reasoning | Not measured | 91.7% | Only GPT-5.6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 33.3% | Only GPT-5.6 Sol measured |
| MMMU Pro (Vals AI) | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 79.0% | 94.1% | GPT-5.6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 49.5% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | Not measured | 93.5% | Only GPT-5.6 Sol measured |
| ARC-AGI | 33.3% | 97.5% | GPT-5.6 Sol |
| ARC-AGI-2 | 2.5% | 92.5% | GPT-5.6 Sol |
| SimpleBench | 41.2% | 64.8% | GPT-5.6 Sol |
| Chess puzzles | Not measured | 59.0% | Only GPT-5.6 Sol measured |
| Mystery game puzzles | Not measured | 58.0% | Only GPT-5.6 Sol measured |
| EBR-bench | Not measured | 44.8% | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | 1422 | 1483 | GPT-5.6 Sol |
| LMArena Text: expert | 1426 | 1517 | GPT-5.6 Sol |
| LMArena Text: hard prompts in English | 1420 | 1477 | GPT-5.6 Sol |
| LMArena Vision: diagrams | 1245 | 1305 | GPT-5.6 Sol |
| LMArena Vision: homework | 1244 | 1305 | GPT-5.6 Sol |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | Not measured | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | 73.3% | Not measured | Only Gemini 2.5 Flash measured |
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-5.6 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| FrontierMath, tier 4 | Not measured | 82.9% | Only GPT-5.6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-5.6 Sol measured |
| LMArena Text: math | 1411 | 1473 | GPT-5.6 Sol |
| LMArena Text: mathematical work | 1422 | 1496 | GPT-5.6 Sol |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| LegalBench (Vals AI) | Not measured | 87.0% | Only GPT-5.6 Sol measured |
| CorpFin (Vals AI) | Not measured | 64.4% | Only GPT-5.6 Sol measured |
| TaxEval (Vals AI) | Not measured | 74.8% | Only GPT-5.6 Sol measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | 40.4% | 44.0% | GPT-5.6 Sol |
| MMLU Pro (Artificial Analysis run) | 83.2% | Not measured | Only Gemini 2.5 Flash measured |
| SimpleQA Verified | Not measured | 69.7% | Only GPT-5.6 Sol measured |
| LMArena Text: science | 1433 | 1455 | GPT-5.6 Sol |
| LMArena Text: medicine and healthcare | 1428 | 1431 | GPT-5.6 Sol |
| LMArena Text: legal and government | 1430 | 1476 | GPT-5.6 Sol |
| LMArena Text: business and finance | 1404 | 1457 | GPT-5.6 Sol |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | 1321 | GPT-5.6 Sol |
| Design Arena: UI components | 1005 | 1338 | GPT-5.6 Sol |
| Design Arena: game dev | 1005 | 1368 | GPT-5.6 Sol |
| Design Arena: data viz | 1060 | 1323 | GPT-5.6 Sol |
| Design Arena: 3D | 1021 | 1385 | GPT-5.6 Sol |
| Design Arena: all code categories | 1059 | 1341 | GPT-5.6 Sol |
| Design Arena: SVG | 1018 | 1316 | GPT-5.6 Sol |
| Design Arena: ASCII art | Not measured | 1302 | Only GPT-5.6 Sol measured |
| LiveBench design | Not measured | 81.6% | Only GPT-5.6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index029
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.8% | Only GPT-5.6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 66.5% | Only GPT-5.6 Sol measured |
| SAGE (Vals AI) | 44.8% | 52.6% | GPT-5.6 Sol |
| MedScribe (Vals AI) | 83.0% | 85.2% | GPT-5.6 Sol |
| Vals Multimodal Index | Not measured | 72.6% | Only GPT-5.6 Sol measured |
| IFBench | 50.3% | 72.7% | GPT-5.6 Sol |
| Long context reasoning (AA-LCR) | 65.3% | 84.0% | GPT-5.6 Sol |
| DTBench | 76.5% | 95.7% | GPT-5.6 Sol |
| LMCA | 27.5% | 58.5% | GPT-5.6 Sol |
| Surface Evolver Bench | Not measured | 93.1% | Only GPT-5.6 Sol measured |
| Furniture assembly | Not measured | 56.7% | Only GPT-5.6 Sol measured |
| LMArena Text | 1417 | 1457 | GPT-5.6 Sol |
| LMArena Text: instruction following | 1405 | 1483 | GPT-5.6 Sol |
| LMArena Text: creative writing | 1400 | 1449 | GPT-5.6 Sol |
| LMArena Vision | 1235 | 1281 | GPT-5.6 Sol |
| LMArena Text: English | 1418 | 1457 | GPT-5.6 Sol |
| LMArena Text: non-English | 1409 | 1451 | GPT-5.6 Sol |
| LMArena Text: Chinese | 1449 | 1525 | GPT-5.6 Sol |
| LMArena Text: German | 1417 | 1476 | GPT-5.6 Sol |
| LMArena Text: Japanese | 1396 | 1472 | GPT-5.6 Sol |
| LMArena Text: Korean | 1385 | 1442 | GPT-5.6 Sol |
| LMArena Text: French | 1432 | 1472 | GPT-5.6 Sol |
| LMArena Text: Spanish | 1422 | 1443 | GPT-5.6 Sol |
| LMArena Text: Russian | 1415 | 1471 | GPT-5.6 Sol |
| LMArena Text: Polish | 1413 | 1459 | GPT-5.6 Sol |
| LMArena Text: multi-turn | 1408 | 1461 | GPT-5.6 Sol |
| LMArena Text: longer queries | 1419 | 1481 | GPT-5.6 Sol |
| LMArena Text: writing and language | 1405 | 1462 | GPT-5.6 Sol |
| LMArena Text: entertainment and media | 1393 | 1450 | GPT-5.6 Sol |
| LMArena Vision: English | 1239 | 1280 | GPT-5.6 Sol |
| LMArena Vision: Chinese | 1284 | 1313 | GPT-5.6 Sol |
| LMArena Vision: reading text | 1237 | 1290 | GPT-5.6 Sol |
| LMArena Vision: humor | 1225 | 1246 | GPT-5.6 Sol |
| LMArena Vision: captioning | 1277 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | 1252 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1241 | 1283 | GPT-5.6 Sol |
| LMArena Document | Not measured | 1483 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 9 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Sol | 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 2.5 Flash$0.0015Fits in one request
GPT-5.6 Sol$0.014Fits in one request
Gemini 2.5 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash$0.022Fits in one request
GPT-5.6 Sol$0.260Fits in one request
Gemini 2.5 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash$0.085Fits in one request
GPT-5.6 Sol$1.00Fits in one request
Gemini 2.5 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 2.5 Flash | OpenAI GPT-5.6 Sol |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | July 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $4.00 |
| Output $/Mtok | $2.50 | $20.00 |
| Coding index | 28.7 | 76.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.466 | $1.20 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than GPT-5.6 Sol for coding?
Pick GPT-5.6 Sol for coding: it scores 76.7 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash. Pick Gemini 2.5 Flash when output tokens cost 8.0x less, or when a solved task costs $0.466 against $1.20.
Which is cheaper, Gemini 2.5 Flash or GPT-5.6 Sol?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Per solved SWE-bench Verified task, Gemini 2.5 Flash costs $0.466 and GPT-5.6 Sol $1.20.
Which has the bigger context window, Gemini 2.5 Flash or GPT-5.6 Sol?
GPT-5.6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Flash vs GPT-5.6 Sol comparison based on?
61 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 1 independent benchmark and GPT-5.6 Sol's on 2. Where only one model has a result, the page says so instead of naming a winner.