Gemini 2.5 Pro vs o1
Updated October 21, 2026. 49 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick o1 for coding: it scores 61.7 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro, though on 1 benchmark against 2.
Pick Gemini 2.5 Pro when output tokens cost 6.0x less, or when the context window is larger, 1.05M against 200K tokens.
- Shared results
- 49
- Gemini 2.5 Pro only
- 38
- o1 only
- 19
- Like-for-like categories
- 7 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
o1
o1 scores 61.7 against 37.0.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 2.5 Pro
Gemini 2.5 Pro leads, 16.1 against 15.2.
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
Reasoning
GPQA Diamond
No call
Only o1 has a GPQA Diamond result, 73.2%.
Directional only
Math
AIME
No call
Only o1 has a AIME result, 71.5%.
Directional only
Knowledge
MMLU Pro
No call
Only o1 has a MMLU Pro result, 83.5%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 2.5 Pro has a Design Arena: websites result, 1167.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Pro
Gemini 2.5 Pro $0.0063, o1 $0.045 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 37.0 from 2 benchmarks, o1 61.7 from 1 benchmark.
- Widest category
- Knowledge, 15.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena Text: German: Gemini 2.5 Pro 1487 against o1 1337, 25.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against o1 $60.00 per million output tokens, 6.0x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, o1 200K.
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 | o1 | Ties |
|---|---|---|---|---|
| Coding | 5 | 1 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 7 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 23 | 1 | ||
| All shared boards | 46 | 3 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index51
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 61.7% | Only o1 measured |
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | Not measured | Only Gemini 2.5 Pro measured |
| AA Coding Index | 33.3 | 39.7 | o1 |
| LiveCodeBench (Vals AI) | Not measured | 50.3% | Only o1 measured |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Vibe Code Bench (Vals AI) | 0.4% | Not measured | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | 67.9% | Gemini 2.5 Pro |
| SciCode | 46.3% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 12.9% | Gemini 2.5 Pro |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | 46.1% | Gemini 2.5 Pro |
| LMArena Text: coding | 1452 | 1367 | Gemini 2.5 Pro |
| LMArena Text: software and IT | 1459 | 1366 | Gemini 2.5 Pro |
| LMArena WebDev: HTML | 1235 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 15.2 | Gemini 2.5 Pro |
| Epoch Capabilities Index | 145.1 | 141.7 | Gemini 2.5 Pro |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| τ²-Bench Telecom | 54.1% | 62.6% | o1 |
| METR time horizons | Not measured | 51.1% | Only o1 measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 73.2% | Only o1 measured |
| MMMU Pro (Vals AI) | Not measured | 77.4% | Only o1 measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | 74.7% | Gemini 2.5 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 7.0% | Gemini 2.5 Pro |
| GPQA Diamond (Epoch AI run) | 85.3% | 76.8% | Gemini 2.5 Pro |
| ARC-AGI | 41.0% | 30.7% | Gemini 2.5 Pro |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleBench | Not measured | 40.1% | Only o1 measured |
| Chess puzzles | Not measured | 10.0% | Only o1 measured |
| VPCT | Not measured | 37.0% | Only o1 measured |
| LMArena Text: hard prompts | 1455 | 1371 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1361 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1372 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | 1281 | 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 index40
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| AIME | Not measured | 71.5% | Only o1 measured |
| MATH 500 (Vals AI) | Not measured | 90.4% | Only o1 measured |
| MGSM (Vals AI) | Not measured | 89.3% | Only o1 measured |
| 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% | 73.3% | Gemini 2.5 Pro |
| FrontierMath, tiers 1 to 3 | 24.6% | 14.7% | Gemini 2.5 Pro |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| MATH level 5 | Not measured | 94.7% | Only o1 measured |
| LMArena Text: math | 1450 | 1388 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1390 | Gemini 2.5 Pro |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 83.5% | Only o1 measured |
| LegalBench (Vals AI) | Not measured | 80.4% | Only o1 measured |
| 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 |
| TaxEval (Vals AI) | Not measured | 74.3% | Only o1 measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedQA (Vals AI) | Not measured | 96.5% | Only o1 measured |
| MedCode (Vals AI) | 50.6% | Not measured | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | 84.1% | Gemini 2.5 Pro |
| SimpleQA Verified | Not measured | 41.1% | Only o1 measured |
| GeoBench | Not measured | 80.0% | Only o1 measured |
| LMArena Text: science | 1480 | 1369 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1355 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1368 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1328 | Gemini 2.5 Pro |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: UI components | 1139 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: game dev | 1112 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: data viz | 1222 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: 3D | 1080 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: all code categories | 1152 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index231
| Benchmark | Gemini 2.5 Pro | o1 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | Not measured | Only Gemini 2.5 Pro measured |
| IFBench | 48.7% | 70.3% | o1 |
| Long context reasoning (AA-LCR) | 69.0% | 65.0% | Gemini 2.5 Pro |
| DTBench | 82.4% | 74.7% | Gemini 2.5 Pro |
| LMCA | 34.8% | 22.3% | Gemini 2.5 Pro |
| Fiction.LiveBench | Not measured | 83.3% | Only o1 measured |
| Creative writing (Lech Mazur) | 83.8% | 70.2% | Gemini 2.5 Pro |
| LMArena Text | 1458 | 1366 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1367 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1347 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1168 | Gemini 2.5 Pro |
| LMArena Text: English | 1458 | 1372 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1358 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1394 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1337 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1346 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | 1396 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1344 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1345 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1356 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | 1355 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1378 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1360 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1358 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1162 | Gemini 2.5 Pro |
| LMArena Vision: Chinese | 1300 | 1235 | Gemini 2.5 Pro |
| LMArena Vision: reading text | 1270 | Not measured | Only Gemini 2.5 Pro measured |
| 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 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | o1 | 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 costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro costs less
Agent loop
200K input + 10K output tokens
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 o1 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | December 17, 2024 |
| Context window | 1.05M | 200K |
| Input $/Mtok | $1.25 | $15.00 |
| Output $/Mtok | $10.00 | $60.00 |
| Coding index | 37.0 | 61.7 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than o1 for coding?
Pick o1 for coding: it scores 61.7 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro, though on 1 benchmark against 2. Pick Gemini 2.5 Pro when output tokens cost 6.0x less, or when the context window is larger, 1.05M against 200K tokens.
Which is cheaper, Gemini 2.5 Pro or o1?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; o1 costs $15.00 and $60.00. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or o1?
Gemini 2.5 Pro, with 1.05M tokens against 200K.
How many benchmarks is the Gemini 2.5 Pro vs o1 comparison based on?
49 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks and o1's on 1. Where only one model has a result, the page says so instead of naming a winner.