Gemini 2.5 Pro vs GPT-6 Sol
GPT-6 Sol leads Gemini 2.5 Pro on coding, 76.0 to 19.1 on the Vibe Coding Index, at about the same output price ($10.00 vs $10.00 per million). Updated October 22, 2026; 62 benchmarks have a result for both.
vs boards won of 62 shared
Gemini 2.5 Pro or GPT-6 Sol: which to pick
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Model AGemini 2.5 ProGoogle19.1/1003 independent benchmarks$0.64 per solved taskModel BGPT-6 SolOpenAI76.0/1005 independent benchmarksNo cost per solved task
- Shared results
- 62
- Gemini 2.5 Pro only
- 28
- GPT-6 Sol only
- 39
- Like-for-like categories
- 8 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
GPT-6 Sol
GPT-6 Sol scores 76.0 against 19.1.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 2.5 Pro has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
GPT-6 Sol
GPT-6 Sol leads, 1292 against 1167.
Same board, both measured
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Pro
Gemini 2.5 Pro $0.0063, GPT-6 Sol $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, GPT-6 Sol 76.0 from 5 benchmarks.
- Widest category
- Agentic work, 86.6 points apart on average over 1 shared benchmark.
- Widest single gap
- FrontierMath, tier 4: Gemini 2.5 Pro 0.0% against GPT-6 Sol 90.0%, 90.0 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, GPT-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 Pro | Bars | GPT-6 Sol | Ties |
|---|---|---|---|---|
| Coding | 2 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 4 | 5 | ||
| Math | 2 | 3 | ||
| Knowledge | 5 | 1 | ||
| Web design | 0 | 6 | ||
| General | 21 | 5 | ||
| All shared boards | 34 | 28 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index25
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LiveBench coding | Not measured | 93.1% | Only GPT-6 Sol measured |
| LMArena WebDev | 1226 | 1683 | GPT-6 Sol |
| AA Coding Index | 33.3 | Not measured | Only Gemini 2.5 Pro measured |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 44.4% | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | 0.4% | 87.8% | GPT-6 Sol |
| Code migration (Vals AI) | Not measured | 57.2% | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only GPT-6 Sol measured |
| IOI (Vals AI) | Not measured | 82.6% | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 83.2% | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | Not measured | 78.0% | Only GPT-6 Sol measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 57.6% | GPT-6 Sol |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierCode | Not measured | 49.3% | Only GPT-6 Sol measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| ALE-Bench | Not measured | 2462.0 | Only GPT-6 Sol measured |
| LMArena Text: coding | 1452 | 1448 | Gemini 2.5 Pro |
| LMArena Text: software and IT | 1459 | 1433 | Gemini 2.5 Pro |
| LMArena WebDev: React | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | 1235 | 1685 | GPT-6 Sol |
| LMArena WebDev: from an image | 1285 | 1660 | GPT-6 Sol |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 47.6 | GPT-6 Sol |
| Epoch Capabilities Index | 145.1 | 163.7 | GPT-6 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: agents building web apps | Not measured | 1231 | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1238 | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1217 | Only GPT-6 Sol measured |
| LiveBench research | Not measured | 69.3% | Only GPT-6 Sol measured |
| LiveBench browser | Not measured | 92.0% | Only GPT-6 Sol measured |
| LiveBench long agentic | Not measured | 66.9% | Only GPT-6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 49.0% | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.0% | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 28.9% | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.5% | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 74.8% | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 30.0% | Only GPT-6 Sol measured |
| Vals Science Index | Not measured | 45.0% | Only GPT-6 Sol measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| APEX-Agents | Not measured | 54.3% | Only GPT-6 Sol measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| SpireClimb | Not measured | 7.5% | Only GPT-6 Sol measured |
| Vending-Bench 2 | $574 | $14,428 | GPT-6 Sol |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index45
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 30.2% | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | Not measured | Only Gemini 2.5 Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 47.9% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | 85.3% | 94.3% | GPT-6 Sol |
| ARC-AGI | 41.0% | 95.5% | GPT-6 Sol |
| ARC-AGI-2 | 4.9% | 89.6% | GPT-6 Sol |
| Chess puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| Mystery game puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| EBR-bench | Not measured | 53.3% | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1455 | 1422 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1437 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1420 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | 1270 | Gemini 2.5 Pro |
| LMArena Vision: homework | 1281 | 1286 | GPT-6 Sol |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | 100.0% | GPT-6 Sol |
| FrontierMath, tiers 1 to 3 | 24.6% | 89.8% | GPT-6 Sol |
| FrontierMath, tier 4 | 0.0% | 90.0% | GPT-6 Sol |
| ProofBench | Not measured | 83.0% | Only GPT-6 Sol measured |
| LMArena Text: math | 1450 | 1407 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1424 | Gemini 2.5 Pro |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | 47.1% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 60.7% | Only GPT-6 Sol measured |
| LMArena Text: science | 1480 | 1389 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1366 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1396 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1380 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | 72.5% | GPT-6 Sol |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1292 | GPT-6 Sol |
| Design Arena: UI components | 1137 | 1290 | GPT-6 Sol |
| Design Arena: game dev | 1111 | 1311 | GPT-6 Sol |
| Design Arena: data viz | 1222 | 1269 | GPT-6 Sol |
| Design Arena: 3D | 1080 | 1314 | GPT-6 Sol |
| Design Arena: all code categories | 1152 | 1300 | GPT-6 Sol |
| Design Arena: SVG | Not measured | 1315 | Only GPT-6 Sol measured |
| Design Arena: ASCII art | Not measured | 1222 | Only GPT-6 Sol measured |
| LiveBench design | Not measured | 82.2% | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index215
| Benchmark | Gemini 2.5 Pro | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.2% | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 56.6% | Only GPT-6 Sol measured |
| SAGE (Vals AI) | 41.9% | 44.8% | GPT-6 Sol |
| MedScribe (Vals AI) | 73.5% | 82.0% | GPT-6 Sol |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | 83.7% | GPT-6 Sol |
| DTBench | 82.4% | 97.3% | GPT-6 Sol |
| LMCA | 34.8% | 59.1% | GPT-6 Sol |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| Furniture assembly | Not measured | 58.3% | Only GPT-6 Sol measured |
| LMArena Text | 1458 | 1398 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1413 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1378 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1240 | Gemini 2.5 Pro |
| LMArena Text: English | 1458 | 1396 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1388 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1412 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1379 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1377 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | 1336 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1399 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1387 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1402 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | 1372 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1414 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1416 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1389 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1373 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1229 | Gemini 2.5 Pro |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | 1258 | Gemini 2.5 Pro |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | 1219 | Gemini 2.5 Pro |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro 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 2.5 Pro | GPT-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 Pro$0.0063Fits in one request
GPT-6 Sol$0.0070Fits in one request
Gemini 2.5 Pro costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro$0.092Fits in one request
GPT-6 Sol$0.130Fits in one request
Gemini 2.5 Pro costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Pro$0.350Fits in one request
GPT-6 Sol$0.500Fits in one request
Gemini 2.5 Pro 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 Pro | OpenAI GPT-6 Sol |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | September 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.25 | $2.00 |
| Output $/Mtok | $10.00 | $10.00 |
| Coding index | 19.1 | 76.0 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than GPT-6 Sol for coding?
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Gemini 2.5 Pro or GPT-6 Sol?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-6 Sol costs $2.00 and $10.00. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or GPT-6 Sol?
GPT-6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Pro vs GPT-6 Sol comparison based on?
62 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and GPT-6 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.