Gemini 3.1 Pro Preview vs GPT-5.5
Updated October 21, 2026. 118 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-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 35.3 for Gemini 3.1 Pro Preview.
Pick Gemini 3.1 Pro Preview when output tokens cost 2.5x less, or when a solved task costs $0.99 against $1.65.
- Shared results
- 118
- Gemini 3.1 Pro Preview only
- 13
- GPT-5.5 only
- 14
- 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-5.5
GPT-5.5 scores 67.8 against 35.3.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 29.7.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.5
GPT-5.5 leads, 36.4 against 8.2.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview leads, 95.5% against 93.2%.
Same board, both measured
Math
AIME
No call
Only Gemini 3.1 Pro Preview has a AIME result, 98.1%.
Directional only
Knowledge
MMLU Pro
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview leads, 91.0% against 88.1%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.5
GPT-5.5 leads, 1256 against 1234.
Same board, both measured
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview $0.0080, GPT-5.5 $0.020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview $0.99, GPT-5.5 $1.65.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.1 Pro Preview 35.3 from 1 benchmark, GPT-5.5 67.8 from 2 benchmarks.
- Widest category
- Math, 18.3 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: Gemini 3.1 Pro Preview 26.8% against GPT-5.5 72.5%, 45.7 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.1 Pro Preview $12.00 against GPT-5.5 $30.00 per million output tokens, 2.5x apart.
- Context window
- Gemini 3.1 Pro Preview takes 1.05M tokens, GPT-5.5 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 3.1 Pro Preview | Bars | GPT-5.5 | Ties |
|---|---|---|---|---|
| Coding | 2 | 18 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 4 | 15 | ||
| Reasoning | 6 | 10 | ||
| Math | 1 | 5 | ||
| Knowledge | 7 | 5 | ||
| Web design | 3 | 5 | ||
| General | 18 | 18 | ||
| All shared boards | 41 | 77 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index218
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 85.1% | Only GPT-5.5 measured |
| LMArena WebDev | 1447 | 1513 | GPT-5.5 |
| AA Coding Index | 68.8 | 74.9 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 88.5% | 85.3% | Gemini 3.1 Pro Preview |
| SWE-bench Verified (Vals AI) | 78.8% | 82.6% | GPT-5.5 |
| Terminal-Bench 4 (Vals AI) | 2.5% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vibe Code Bench (Vals AI) | 32.0% | 69.8% | GPT-5.5 |
| Code migration (Vals AI) | 17.3% | 45.2% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.0% | 0.5% | GPT-5.5 |
| IOI (Vals AI) | 51.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Terminal-Bench 2.1 (Vals AI) | 70.8% | 76.4% | GPT-5.5 |
| Vibe Code Bench 1-100 (Vals AI) | 6.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| SkillsBench (Vals AI) | Not measured | 62.5% | Only GPT-5.5 measured |
| SciCode | 58.7% | 56.1% | Gemini 3.1 Pro Preview |
| Terminal-Bench Hard (Artificial Analysis run) | 53.8% | 60.6% | GPT-5.5 |
| Terminal-Bench | 80.2% | 84.7% | GPT-5.5 |
| FrontierCode | Not measured | 43.0% | Only GPT-5.5 measured |
| GSO-Bench | 22.6% | 40.2% | GPT-5.5 |
| WeirdML | 72.1% | 84.9% | GPT-5.5 |
| MirrorCode | 8.9% | 10.0% | GPT-5.5 |
| ALE-Bench | 1160.6 | 1943.0 | GPT-5.5 |
| LMArena Text: coding | 1484 | 1494 | GPT-5.5 |
| LMArena Text: software and IT | 1487 | 1493 | GPT-5.5 |
| LMArena WebDev: React | 1438 | 1506 | GPT-5.5 |
| LMArena WebDev: HTML | 1490 | 1543 | GPT-5.5 |
| LMArena WebDev: from an image | 1481 | 1532 | GPT-5.5 |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.7 | 38.4 | GPT-5.5 |
| Epoch Capabilities Index | Not measured | 159.7 | Only GPT-5.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index415
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 8.2 | 36.4 | GPT-5.5 |
| Design Arena: agents building web apps | 1125 | 1117 | Gemini 3.1 Pro Preview |
| Design Arena: agents building full-stack apps | 1068 | 1089 | GPT-5.5 |
| Design Arena: agents building mobile apps | 1094 | 1143 | GPT-5.5 |
| Design Arena: agents building Android apps | 1055 | 1169 | GPT-5.5 |
| Design Arena: agents building Godot games | 1236 | 1173 | Gemini 3.1 Pro Preview |
| Design Arena: agents building games | 1114 | 1179 | GPT-5.5 |
| Design Arena: HTML slides | 1153 | 1067 | Gemini 3.1 Pro Preview |
| Design Arena: PowerPoint slides | 1064 | 1108 | GPT-5.5 |
| LiveBench research | Not measured | 61.6% | Only GPT-5.5 measured |
| LiveBench browser | Not measured | 48.0% | Only GPT-5.5 measured |
| LiveBench long agentic | Not measured | 44.6% | Only GPT-5.5 measured |
| SREBench (Vals AI) | 0.0% | 3.8% | GPT-5.5 |
| Finance Agent (Vals AI) | 43.0% | 51.8% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 9.3% | 21.8% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 20.7% | 40.4% | GPT-5.5 |
| Excel Modeling Benchmark (Vals AI) | 52.6% | 64.5% | GPT-5.5 |
| BioMysteryBench (Vals AI) | 60.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Terminal-Bench-Science (Vals AI) | 1.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Vals Science Index | 27.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Time Horizon Index (Vals AI) | Not measured | 8.3% | Only GPT-5.5 measured |
| τ²-Bench Telecom | 95.6% | 93.9% | Gemini 3.1 Pro Preview |
| APEX-Agents | 35.1% | 55.1% | GPT-5.5 |
| METR time horizons | 77.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Remote Labor Index | Not measured | 6.3% | Only GPT-5.5 measured |
| OSWorld 2.0 | Not measured | 13.0% | Only GPT-5.5 measured |
| BALROG | 57.0% | Not measured | Only Gemini 3.1 Pro Preview measured |
| DeepResearch Bench | 47.8% | 54.0% | GPT-5.5 |
| PostTrainBench | 22.0% | 27.2% | GPT-5.5 |
| Vending-Bench 2 | $911 | $7,524 | GPT-5.5 |
| Neither model has a result on the other 9 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index610
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 95.5% | 93.2% | Gemini 3.1 Pro Preview |
| LiveBench reasoning | Not measured | 89.7% | Only GPT-5.5 measured |
| MysteryMechanism (Vals AI) | 20.7% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MMMU Pro (Vals AI) | 88.2% | 88.3% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 94.1% | 93.5% | Gemini 3.1 Pro Preview |
| Humanity's Last Exam (Artificial Analysis run) | 47.0% | 45.8% | Gemini 3.1 Pro Preview |
| GPQA Diamond (Epoch AI run) | 94.4% | 90.7% | Gemini 3.1 Pro Preview |
| ARC-AGI | 98.0% | 95.0% | Gemini 3.1 Pro Preview |
| ARC-AGI-2 | 77.1% | 85.0% | GPT-5.5 |
| SimpleBench | 79.6% | 69.0% | Gemini 3.1 Pro Preview |
| Chess puzzles | 51.0% | 63.0% | GPT-5.5 |
| Mystery game puzzles | 34.0% | 56.0% | GPT-5.5 |
| EBR-bench | 14.3% | 34.3% | GPT-5.5 |
| LMArena Text: hard prompts | 1485 | 1489 | GPT-5.5 |
| LMArena Text: expert | 1483 | 1507 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1480 | 1483 | GPT-5.5 |
| LMArena Vision: diagrams | 1311 | 1325 | GPT-5.5 |
| LMArena Vision: homework | 1316 | 1332 | GPT-5.5 |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AIME | 98.1% | Not measured | Only Gemini 3.1 Pro Preview measured |
| OTIS Mock AIME | 95.6% | 84.4% | Gemini 3.1 Pro Preview |
| FrontierMath, tiers 1 to 3 | 59.6% | 85.3% | GPT-5.5 |
| FrontierMath, tier 4 | 26.8% | 72.5% | GPT-5.5 |
| ProofBench | 26.0% | 50.0% | GPT-5.5 |
| LMArena Text: math | 1486 | 1487 | GPT-5.5 |
| LMArena Text: mathematical work | 1478 | 1496 | GPT-5.5 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index75
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| MMLU Pro | 91.0% | 88.1% | Gemini 3.1 Pro Preview |
| LegalBench (Vals AI) | 87.4% | 86.5% | Gemini 3.1 Pro Preview |
| CaseLaw (Vals AI) | 64.8% | 66.2% | GPT-5.5 |
| CorpFin (Vals AI) | 64.5% | 68.4% | GPT-5.5 |
| TaxEval (Vals AI) | 72.9% | 75.0% | GPT-5.5 |
| MortgageTax (Vals AI) | 69.4% | 68.8% | Gemini 3.1 Pro Preview |
| MedQA (Vals AI) | 96.4% | Not measured | Only Gemini 3.1 Pro Preview measured |
| MedCode (Vals AI) | 59.1% | 49.1% | Gemini 3.1 Pro Preview |
| SimpleQA Verified | 73.5% | 63.0% | Gemini 3.1 Pro Preview |
| LMArena Text: science | 1497 | 1485 | Gemini 3.1 Pro Preview |
| LMArena Text: medicine and healthcare | 1486 | 1465 | Gemini 3.1 Pro Preview |
| LMArena Text: legal and government | 1487 | 1491 | GPT-5.5 |
| LMArena Text: business and finance | 1459 | 1478 | GPT-5.5 |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index35
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1234 | 1256 | GPT-5.5 |
| Design Arena: UI components | 1226 | 1260 | GPT-5.5 |
| Design Arena: game dev | 1203 | 1294 | GPT-5.5 |
| Design Arena: data viz | 1209 | 1265 | GPT-5.5 |
| Design Arena: 3D | 1234 | 1198 | Gemini 3.1 Pro Preview |
| Design Arena: all code categories | 1231 | 1260 | GPT-5.5 |
| Design Arena: SVG | 1285 | 1234 | Gemini 3.1 Pro Preview |
| Design Arena: ASCII art | 1270 | 1254 | Gemini 3.1 Pro Preview |
| LiveBench design | Not measured | 70.3% | Only GPT-5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index1818
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.6% | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | 53.8% | 60.9% | GPT-5.5 |
| SAGE (Vals AI) | 48.7% | 51.5% | GPT-5.5 |
| MedScribe (Vals AI) | 76.1% | 86.9% | GPT-5.5 |
| Vals Multimodal Index | 56.1% | 68.1% | GPT-5.5 |
| IFBench | 77.1% | 75.9% | Gemini 3.1 Pro Preview |
| Long context reasoning (AA-LCR) | 82.0% | 84.3% | GPT-5.5 |
| DTBench | 97.1% | 96.0% | Gemini 3.1 Pro Preview |
| LMCA | 53.8% | 54.3% | GPT-5.5 |
| CL-bench | 20.8% | Not measured | Only Gemini 3.1 Pro Preview measured |
| Surface Evolver Bench | Not measured | 88.1% | Only GPT-5.5 measured |
| Furniture assembly | 26.7% | 44.2% | GPT-5.5 |
| ExploitBench | 26.1% | 47.4% | GPT-5.5 |
| CL-bench Life | 16.9% | 22.2% | GPT-5.5 |
| LMArena Text | 1480 | 1471 | Gemini 3.1 Pro Preview |
| LMArena Text: instruction following | 1466 | 1478 | GPT-5.5 |
| LMArena Text: creative writing | 1482 | 1455 | Gemini 3.1 Pro Preview |
| LMArena Vision | 1296 | 1297 | GPT-5.5 |
| LMArena Text: English | 1478 | 1470 | Gemini 3.1 Pro Preview |
| LMArena Text: non-English | 1476 | 1467 | Gemini 3.1 Pro Preview |
| LMArena Text: Chinese | 1527 | 1534 | GPT-5.5 |
| LMArena Text: German | 1490 | 1480 | Gemini 3.1 Pro Preview |
| LMArena Text: Japanese | 1491 | 1499 | GPT-5.5 |
| LMArena Text: Korean | 1455 | 1460 | GPT-5.5 |
| LMArena Text: French | 1487 | 1485 | Gemini 3.1 Pro Preview |
| LMArena Text: Spanish | 1481 | 1468 | Gemini 3.1 Pro Preview |
| LMArena Text: Russian | 1497 | 1473 | Gemini 3.1 Pro Preview |
| LMArena Text: Polish | 1498 | 1465 | Gemini 3.1 Pro Preview |
| LMArena Text: multi-turn | 1487 | 1476 | Gemini 3.1 Pro Preview |
| LMArena Text: longer queries | 1482 | 1484 | GPT-5.5 |
| LMArena Text: writing and language | 1481 | 1466 | Gemini 3.1 Pro Preview |
| LMArena Text: entertainment and media | 1465 | 1449 | Gemini 3.1 Pro Preview |
| LMArena Vision: English | 1287 | 1292 | GPT-5.5 |
| LMArena Vision: Chinese | 1364 | 1360 | Gemini 3.1 Pro Preview |
| LMArena Vision: reading text | 1304 | 1306 | GPT-5.5 |
| LMArena Vision: humor | 1322 | 1293 | Gemini 3.1 Pro Preview |
| LMArena Vision: captioning | 1345 | Not measured | Only Gemini 3.1 Pro Preview measured |
| LMArena Vision: recognizing things | 1330 | 1231 | Gemini 3.1 Pro Preview |
| LMArena Vision: creative writing | 1324 | 1301 | Gemini 3.1 Pro Preview |
| LMArena Document | 1444 | 1486 | GPT-5.5 |
| Neither model has a result on the other 6 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.1 Pro Preview | GPT-5.5 | 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 3.1 Pro Preview costs less
Repository review
50K input + 3K output tokens
Gemini 3.1 Pro Preview costs less
Agent loop
200K input + 10K output tokens
Gemini 3.1 Pro Preview 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 3.1 Pro Preview | OpenAI GPT-5.5 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | February 19, 2026 | April 24, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $5.00 |
| Output $/Mtok | $12.00 | $30.00 |
| Coding index | 35.3 | 67.8 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.99 | $1.65 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.1 Pro Preview better than GPT-5.5 for coding?
Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 35.3 for Gemini 3.1 Pro Preview. Pick Gemini 3.1 Pro Preview when output tokens cost 2.5x less, or when a solved task costs $0.99 against $1.65.
Which is cheaper, Gemini 3.1 Pro Preview or GPT-5.5?
Gemini 3.1 Pro Preview costs $2.00 per million input tokens and $12.00 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, Gemini 3.1 Pro Preview costs $0.99 and GPT-5.5 $1.65.
Which has the bigger context window, Gemini 3.1 Pro Preview or GPT-5.5?
GPT-5.5, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3.1 Pro Preview vs GPT-5.5 comparison based on?
118 benchmarks have a result for both models as of October 21, 2026. Gemini 3.1 Pro Preview's coding index rests on 1 independent benchmark and GPT-5.5's on 2. Where only one model has a result, the page says so instead of naming a winner.