Gemini 2.5 Pro Preview 06-05 vs GPT-5.1
Updated October 21, 2026. 10 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Gemini 2.5 Pro Preview 06-05 for coding: it scores 83.1 on the Vibe Coding Index against 53.3 for GPT-5.1, though on 1 benchmark against 2.
Pick GPT-5.1 when what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 10
- Gemini 2.5 Pro Preview 06-05 only
- 4
- GPT-5.1 only
- 90
- Like-for-like categories
- 4 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
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 scores 83.1 against 53.3.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.1 has a AA Intelligence Index result, 24.7.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.1 has a GPQA Diamond result, 86.6%.
Directional only
Math
AIME
No call
Only GPT-5.1 has a AIME result, 93.3%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.1 has a MMLU Pro result, 86.4%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.1 has a Design Arena: websites result, 1187.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
Gemini 2.5 Pro Preview 06-05 $0.0063, GPT-5.1 $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1 has the number, $1.02.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro Preview 06-05 83.1 from 1 benchmark, GPT-5.1 53.3 from 2 benchmarks.
- Widest category
- Coding, 8.7 points apart on average over 3 shared benchmarks.
- Widest single gap
- VPCT: Gemini 2.5 Pro Preview 06-05 46.4% against GPT-5.1 58.7%, 12.3 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- Context window
- Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, GPT-5.1 400K.
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 Preview 06-05 | Bars | GPT-5.1 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Agentic work | 0 | 0 | 1 tie | |
| Reasoning | 1 | 4 | ||
| Knowledge | 0 | 1 | ||
| All shared boards | 1 | 8 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| Aider polyglot | 83.1% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SWE-bench Verified | Not measured | 66.0% | Only GPT-5.1 measured |
| LMArena WebDev | Not measured | 1396 | Only GPT-5.1 measured |
| AA Coding Index | Not measured | 49.4 | Only GPT-5.1 measured |
| LiveCodeBench (Vals AI) | 79.2% | 86.5% | GPT-5.1 |
| SWE-bench Verified (Vals AI) | Not measured | 69.8% | Only GPT-5.1 measured |
| Vibe Code Bench (Vals AI) | Not measured | 24.6% | Only GPT-5.1 measured |
| LiveCodeBench (Artificial Analysis run) | 77.8% | 86.8% | GPT-5.1 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 45.5% | Only GPT-5.1 measured |
| Terminal-Bench | Not measured | 47.6% | Only GPT-5.1 measured |
| GSO-Bench | 3.9% | 13.7% | GPT-5.1 |
| WeirdML | Not measured | 60.8% | Only GPT-5.1 measured |
| LMArena Text: coding | Not measured | 1453 | Only GPT-5.1 measured |
| LMArena Text: software and IT | Not measured | 1454 | Only GPT-5.1 measured |
| LMArena WebDev: React | Not measured | 1307 | Only GPT-5.1 measured |
| LMArena WebDev: HTML | Not measured | 1405 | Only GPT-5.1 measured |
| LMArena WebDev: from an image | Not measured | 1421 | Only GPT-5.1 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 24.7 | Only GPT-5.1 measured |
| Epoch Capabilities Index | Not measured | 149.8 | Only GPT-5.1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 81.9% | Only GPT-5.1 measured |
| METR time horizons | 55.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Remote Labor Index | 0.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| DeepResearch Bench | 42.8% | 42.8% | Tie |
| Vending-Bench 2 | Not measured | $1,473 | Only GPT-5.1 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 86.6% | Only GPT-5.1 measured |
| MMMU Pro (Vals AI) | Not measured | 83.2% | Only GPT-5.1 measured |
| GPQA Diamond (Artificial Analysis run) | 83.6% | 87.3% | GPT-5.1 |
| Humanity's Last Exam (Artificial Analysis run) | 19.9% | 28.5% | GPT-5.1 |
| GPQA Diamond (Epoch AI run) | 84.8% | 87.6% | GPT-5.1 |
| ARC-AGI | Not measured | 72.8% | Only GPT-5.1 measured |
| ARC-AGI-2 | Not measured | 17.6% | Only GPT-5.1 measured |
| SimpleBench | 62.4% | 53.2% | Gemini 2.5 Pro Preview 06-05 |
| Chess puzzles | Not measured | 42.0% | Only GPT-5.1 measured |
| Mystery game puzzles | Not measured | 19.0% | Only GPT-5.1 measured |
| VPCT | 46.4% | 58.7% | GPT-5.1 |
| LMArena Text: hard prompts | Not measured | 1457 | Only GPT-5.1 measured |
| LMArena Text: expert | Not measured | 1470 | Only GPT-5.1 measured |
| LMArena Text: hard prompts in English | Not measured | 1462 | Only GPT-5.1 measured |
| LMArena Vision: diagrams | Not measured | 1264 | Only GPT-5.1 measured |
| LMArena Vision: homework | Not measured | 1272 | Only GPT-5.1 measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| AIME | Not measured | 93.3% | Only GPT-5.1 measured |
| MGSM (Vals AI) | Not measured | 93.0% | Only GPT-5.1 measured |
| AA Math Index | Not measured | 94.0 | Only GPT-5.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 94.0% | Only GPT-5.1 measured |
| OTIS Mock AIME | Not measured | 88.6% | Only GPT-5.1 measured |
| LMArena Text: math | Not measured | 1446 | Only GPT-5.1 measured |
| LMArena Text: mathematical work | Not measured | 1449 | Only GPT-5.1 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.4% | Only GPT-5.1 measured |
| LegalBench (Vals AI) | Not measured | 85.7% | Only GPT-5.1 measured |
| CaseLaw (Vals AI) | Not measured | 73.4% | Only GPT-5.1 measured |
| CorpFin (Vals AI) | Not measured | 63.8% | Only GPT-5.1 measured |
| TaxEval (Vals AI) | Not measured | 74.9% | Only GPT-5.1 measured |
| MortgageTax (Vals AI) | Not measured | 61.4% | Only GPT-5.1 measured |
| MedQA (Vals AI) | Not measured | 96.4% | Only GPT-5.1 measured |
| MedCode (Vals AI) | Not measured | 52.7% | Only GPT-5.1 measured |
| MMLU Pro (Artificial Analysis run) | 85.8% | 87.0% | GPT-5.1 |
| SimpleQA Verified | Not measured | 48.0% | Only GPT-5.1 measured |
| LMArena Text: science | Not measured | 1459 | Only GPT-5.1 measured |
| LMArena Text: medicine and healthcare | Not measured | 1456 | Only GPT-5.1 measured |
| LMArena Text: legal and government | Not measured | 1459 | Only GPT-5.1 measured |
| LMArena Text: business and finance | Not measured | 1431 | Only GPT-5.1 measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1187 | Only GPT-5.1 measured |
| Design Arena: UI components | Not measured | 1166 | Only GPT-5.1 measured |
| Design Arena: game dev | Not measured | 1179 | Only GPT-5.1 measured |
| Design Arena: data viz | Not measured | 1204 | Only GPT-5.1 measured |
| Design Arena: 3D | Not measured | 1061 | Only GPT-5.1 measured |
| Design Arena: all code categories | Not measured | 1171 | Only GPT-5.1 measured |
| Design Arena: SVG | Not measured | 1149 | Only GPT-5.1 measured |
| Design Arena: ASCII art | Not measured | 1118 | Only GPT-5.1 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index35 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 43.2% | Only GPT-5.1 measured |
| MedScribe (Vals AI) | Not measured | 88.1% | Only GPT-5.1 measured |
| IFBench | Not measured | 72.9% | Only GPT-5.1 measured |
| Long context reasoning (AA-LCR) | Not measured | 80.0% | Only GPT-5.1 measured |
| DTBench | Not measured | 90.1% | Only GPT-5.1 measured |
| LMCA | Not measured | 43.9% | Only GPT-5.1 measured |
| Fiction.LiveBench | 91.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| CL-bench | Not measured | 23.7% | Only GPT-5.1 measured |
| CL-bench Life | Not measured | 17.3% | Only GPT-5.1 measured |
| LMArena Text | Not measured | 1443 | Only GPT-5.1 measured |
| LMArena Text: instruction following | Not measured | 1443 | Only GPT-5.1 measured |
| LMArena Text: creative writing | Not measured | 1427 | Only GPT-5.1 measured |
| LMArena Vision | Not measured | 1250 | Only GPT-5.1 measured |
| LMArena Text: English | Not measured | 1451 | Only GPT-5.1 measured |
| LMArena Text: non-English | Not measured | 1431 | Only GPT-5.1 measured |
| LMArena Text: Chinese | Not measured | 1495 | Only GPT-5.1 measured |
| LMArena Text: German | Not measured | 1438 | Only GPT-5.1 measured |
| LMArena Text: Japanese | Not measured | 1453 | Only GPT-5.1 measured |
| LMArena Text: Korean | Not measured | 1401 | Only GPT-5.1 measured |
| LMArena Text: French | Not measured | 1450 | Only GPT-5.1 measured |
| LMArena Text: Spanish | Not measured | 1433 | Only GPT-5.1 measured |
| LMArena Text: Russian | Not measured | 1435 | Only GPT-5.1 measured |
| LMArena Text: Polish | Not measured | 1440 | Only GPT-5.1 measured |
| LMArena Text: multi-turn | Not measured | 1450 | Only GPT-5.1 measured |
| LMArena Text: longer queries | Not measured | 1448 | Only GPT-5.1 measured |
| LMArena Text: writing and language | Not measured | 1428 | Only GPT-5.1 measured |
| LMArena Text: entertainment and media | Not measured | 1415 | Only GPT-5.1 measured |
| LMArena Vision: English | Not measured | 1252 | Only GPT-5.1 measured |
| LMArena Vision: Chinese | Not measured | 1270 | Only GPT-5.1 measured |
| LMArena Vision: reading text | Not measured | 1255 | Only GPT-5.1 measured |
| LMArena Vision: humor | Not measured | 1263 | Only GPT-5.1 measured |
| LMArena Vision: captioning | Not measured | 1252 | Only GPT-5.1 measured |
| LMArena Vision: recognizing things | Not measured | 1232 | Only GPT-5.1 measured |
| LMArena Vision: creative writing | Not measured | 1266 | Only GPT-5.1 measured |
| LMArena Document | Not measured | 1403 | Only GPT-5.1 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.1 | 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 Preview 06-05 | OpenAI GPT-5.1 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 5, 2025 | November 13, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $1.25 | $1.25 |
| Output $/Mtok | $10.00 | $10.00 |
| Coding index | 83.1 | 53.3 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $1.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro Preview 06-05 better than GPT-5.1 for coding?
Pick Gemini 2.5 Pro Preview 06-05 for coding: it scores 83.1 on the Vibe Coding Index against 53.3 for GPT-5.1, though on 1 benchmark against 2. Pick GPT-5.1 when what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Gemini 2.5 Pro Preview 06-05 or GPT-5.1?
Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-5.1 costs $1.25 and $10.00. Cost per solved task is known for GPT-5.1 only.
Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or GPT-5.1?
Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs GPT-5.1 comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 1 independent benchmark and GPT-5.1's on 2. Where only one model has a result, the page says so instead of naming a winner.