Gemini 3 Flash Preview vs GPT-5.5
Updated October 21, 2026. 58 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 3 Flash Preview for coding: it scores 75.8 on the Vibe Coding Index against 67.8 for GPT-5.5, though on 1 benchmark against 2.
Pick GPT-5.5 when the context window is larger, 1.05M against 1.05M tokens, or when what matters is SWE-bench Verified (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 58
- Gemini 3 Flash Preview only
- 11
- GPT-5.5 only
- 74
- 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
Gemini 3 Flash Preview
Gemini 3 Flash Preview scores 75.8 against 67.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 26.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.5 has a AA Agentic Index result, 36.4.
Directional only
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 87.9%.
Same board, both measured
Math
AIME
No call
Only Gemini 3 Flash Preview has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
Gemini 3 Flash Preview
Gemini 3 Flash Preview leads, 88.6% against 88.1%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.5
GPT-5.5 leads, 1256 against 1196.
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 Flash Preview
Gemini 3 Flash Preview $0.0020, GPT-5.5 $0.020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3 Flash Preview
Gemini 3 Flash Preview $0.37, GPT-5.5 $1.65.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3 Flash Preview 75.8 from 1 benchmark, GPT-5.5 67.8 from 2 benchmarks.
- Widest category
- Math, 33.9 points apart on average over 4 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: Gemini 3 Flash Preview 17.1% against GPT-5.5 72.5%, 55.4 points apart on a 0 to 100 scale.
- Output price
- Gemini 3 Flash Preview $3.00 against GPT-5.5 $30.00 per million output tokens, 10.0x apart.
- Context window
- Gemini 3 Flash 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 Flash Preview | Bars | GPT-5.5 | Ties |
|---|---|---|---|---|
| Coding | 1 | 10 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 13 | ||
| Reasoning | 0 | 10 | ||
| Math | 1 | 3 | ||
| Knowledge | 4 | 4 | ||
| Web design | 0 | 4 | ||
| General | 2 | 5 | ||
| All shared boards | 8 | 50 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index110
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 75.8% | Not measured | Only Gemini 3 Flash Preview measured |
| LiveBench coding | Not measured | 85.1% | Only GPT-5.5 measured |
| LMArena WebDev | Not measured | 1513 | Only GPT-5.5 measured |
| AA Coding Index | Not measured | 74.9 | Only GPT-5.5 measured |
| LiveCodeBench (Vals AI) | 85.6% | 85.3% | Gemini 3 Flash Preview |
| SWE-bench Verified (Vals AI) | 75.0% | 82.6% | GPT-5.5 |
| Vibe Code Bench (Vals AI) | 20.2% | 69.8% | GPT-5.5 |
| Code migration (Vals AI) | 6.4% | 45.2% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.0% | 0.5% | GPT-5.5 |
| Terminal-Bench 2.1 (Vals AI) | 53.9% | 76.4% | GPT-5.5 |
| SkillsBench (Vals AI) | Not measured | 62.5% | Only GPT-5.5 measured |
| LiveCodeBench (Artificial Analysis run) | 90.8% | Not measured | Only Gemini 3 Flash Preview measured |
| SciCode | Not measured | 56.1% | Only GPT-5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 38.6% | 60.6% | GPT-5.5 |
| Terminal-Bench | 64.3% | 84.7% | GPT-5.5 |
| FrontierCode | Not measured | 43.0% | Only GPT-5.5 measured |
| GSO-Bench | 9.8% | 40.2% | GPT-5.5 |
| WeirdML | 61.6% | 84.9% | GPT-5.5 |
| MirrorCode | Not measured | 10.0% | Only GPT-5.5 measured |
| ALE-Bench | 1367.2 | 1943.0 | GPT-5.5 |
| LMArena Text: coding | Not measured | 1494 | Only GPT-5.5 measured |
| LMArena Text: software and IT | Not measured | 1493 | Only GPT-5.5 measured |
| LMArena WebDev: React | Not measured | 1506 | Only GPT-5.5 measured |
| LMArena WebDev: HTML | Not measured | 1543 | Only GPT-5.5 measured |
| LMArena WebDev: from an image | Not measured | 1532 | Only GPT-5.5 measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.3 | 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 index013
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 36.4 | Only GPT-5.5 measured |
| Design Arena: agents building web apps | 1111 | 1117 | GPT-5.5 |
| Design Arena: agents building full-stack apps | 1063 | 1089 | GPT-5.5 |
| Design Arena: agents building mobile apps | 1090 | 1143 | GPT-5.5 |
| Design Arena: agents building Android apps | 1056 | 1169 | GPT-5.5 |
| Design Arena: agents building Godot games | 1161 | 1173 | GPT-5.5 |
| Design Arena: agents building games | Not measured | 1179 | Only GPT-5.5 measured |
| Design Arena: HTML slides | Not measured | 1067 | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1036 | 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) | Not measured | 3.8% | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 42.5% | 51.8% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 11.8% | 21.8% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 18.3% | 40.4% | GPT-5.5 |
| Excel Modeling Benchmark (Vals AI) | 26.0% | 64.5% | GPT-5.5 |
| Time Horizon Index (Vals AI) | Not measured | 8.3% | Only GPT-5.5 measured |
| τ²-Bench Telecom | 80.4% | 93.9% | GPT-5.5 |
| APEX-Agents | Not measured | 55.1% | Only GPT-5.5 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 | 48.1% | Not measured | Only Gemini 3 Flash Preview measured |
| DeepResearch Bench | 49.8% | 54.0% | GPT-5.5 |
| PostTrainBench | Not measured | 27.2% | Only GPT-5.5 measured |
| Vending-Bench 2 | $3,635 | $7,524 | GPT-5.5 |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 87.9% | 93.2% | GPT-5.5 |
| LiveBench reasoning | Not measured | 89.7% | Only GPT-5.5 measured |
| MMMU Pro (Vals AI) | 87.6% | 88.3% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 89.8% | 93.5% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 36.6% | 45.8% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 89.4% | 90.7% | GPT-5.5 |
| ARC-AGI | 84.7% | 95.0% | GPT-5.5 |
| ARC-AGI-2 | 33.6% | 85.0% | GPT-5.5 |
| SimpleBench | 61.1% | 69.0% | GPT-5.5 |
| Chess puzzles | 39.0% | 63.0% | GPT-5.5 |
| Mystery game puzzles | 26.0% | 56.0% | GPT-5.5 |
| EBR-bench | Not measured | 34.3% | Only GPT-5.5 measured |
| VPCT | 72.6% | Not measured | Only Gemini 3 Flash Preview measured |
| LMArena Text: hard prompts | Not measured | 1489 | Only GPT-5.5 measured |
| LMArena Text: expert | Not measured | 1507 | Only GPT-5.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1483 | Only GPT-5.5 measured |
| LMArena Vision: diagrams | Not measured | 1325 | Only GPT-5.5 measured |
| LMArena Vision: homework | Not measured | 1332 | Only GPT-5.5 measured |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| AIME | 95.6% | Not measured | Only Gemini 3 Flash Preview measured |
| MGSM (Vals AI) | 93.3% | Not measured | Only Gemini 3 Flash Preview measured |
| AA Math Index | 97.0 | Not measured | Only Gemini 3 Flash Preview measured |
| AIME 2025 (Artificial Analysis run) | 97.0% | Not measured | Only Gemini 3 Flash Preview measured |
| OTIS Mock AIME | 95.6% | 84.4% | Gemini 3 Flash Preview |
| FrontierMath, tiers 1 to 3 | 51.2% | 85.3% | GPT-5.5 |
| FrontierMath, tier 4 | 17.1% | 72.5% | GPT-5.5 |
| ProofBench | 15.0% | 50.0% | GPT-5.5 |
| LMArena Text: math | Not measured | 1487 | Only GPT-5.5 measured |
| LMArena Text: mathematical work | Not measured | 1496 | Only GPT-5.5 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| MMLU Pro | 88.6% | 88.1% | Gemini 3 Flash Preview |
| LegalBench (Vals AI) | 86.9% | 86.5% | Gemini 3 Flash Preview |
| CaseLaw (Vals AI) | 55.8% | 66.2% | GPT-5.5 |
| CorpFin (Vals AI) | 66.4% | 68.4% | GPT-5.5 |
| TaxEval (Vals AI) | 73.9% | 75.0% | GPT-5.5 |
| MortgageTax (Vals AI) | 68.7% | 68.8% | GPT-5.5 |
| MedQA (Vals AI) | 95.8% | Not measured | Only Gemini 3 Flash Preview measured |
| MedCode (Vals AI) | 55.9% | 49.1% | Gemini 3 Flash Preview |
| MMLU Pro (Artificial Analysis run) | 89.0% | Not measured | Only Gemini 3 Flash Preview measured |
| SimpleQA Verified | 66.8% | 63.0% | Gemini 3 Flash Preview |
| GeoBench | 88.0% | Not measured | Only Gemini 3 Flash Preview measured |
| LMArena Text: science | Not measured | 1485 | Only GPT-5.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1465 | Only GPT-5.5 measured |
| LMArena Text: legal and government | Not measured | 1491 | Only GPT-5.5 measured |
| LMArena Text: business and finance | Not measured | 1478 | Only GPT-5.5 measured |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1196 | 1256 | GPT-5.5 |
| Design Arena: UI components | Not measured | 1260 | Only GPT-5.5 measured |
| Design Arena: game dev | 1166 | 1294 | GPT-5.5 |
| Design Arena: data viz | Not measured | 1265 | Only GPT-5.5 measured |
| Design Arena: 3D | 1184 | 1198 | GPT-5.5 |
| Design Arena: all code categories | 1189 | 1260 | GPT-5.5 |
| Design Arena: SVG | Not measured | 1234 | Only GPT-5.5 measured |
| Design Arena: ASCII art | Not measured | 1254 | Only GPT-5.5 measured |
| LiveBench design | Not measured | 70.3% | Only GPT-5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Gemini 3 Flash Preview | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.6% | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | Not measured | 60.9% | Only GPT-5.5 measured |
| SAGE (Vals AI) | 51.8% | 51.5% | Gemini 3 Flash Preview |
| MedScribe (Vals AI) | 69.9% | 86.9% | GPT-5.5 |
| Vals Multimodal Index | 52.2% | 68.1% | GPT-5.5 |
| IFBench | 78.0% | 75.9% | Gemini 3 Flash Preview |
| Long context reasoning (AA-LCR) | 78.0% | 84.3% | GPT-5.5 |
| DTBench | 89.1% | 96.0% | GPT-5.5 |
| LMCA | 43.1% | 54.3% | GPT-5.5 |
| Surface Evolver Bench | Not measured | 88.1% | Only GPT-5.5 measured |
| Furniture assembly | Not measured | 44.2% | Only GPT-5.5 measured |
| ExploitBench | Not measured | 47.4% | Only GPT-5.5 measured |
| CL-bench Life | Not measured | 22.2% | Only GPT-5.5 measured |
| LMArena Text | Not measured | 1471 | Only GPT-5.5 measured |
| LMArena Text: instruction following | Not measured | 1478 | Only GPT-5.5 measured |
| LMArena Text: creative writing | Not measured | 1455 | Only GPT-5.5 measured |
| LMArena Vision | Not measured | 1297 | Only GPT-5.5 measured |
| LMArena Text: English | Not measured | 1470 | Only GPT-5.5 measured |
| LMArena Text: non-English | Not measured | 1467 | Only GPT-5.5 measured |
| LMArena Text: Chinese | Not measured | 1534 | Only GPT-5.5 measured |
| LMArena Text: German | Not measured | 1480 | Only GPT-5.5 measured |
| LMArena Text: Japanese | Not measured | 1499 | Only GPT-5.5 measured |
| LMArena Text: Korean | Not measured | 1460 | Only GPT-5.5 measured |
| LMArena Text: French | Not measured | 1485 | Only GPT-5.5 measured |
| LMArena Text: Spanish | Not measured | 1468 | Only GPT-5.5 measured |
| LMArena Text: Russian | Not measured | 1473 | Only GPT-5.5 measured |
| LMArena Text: Polish | Not measured | 1465 | Only GPT-5.5 measured |
| LMArena Text: multi-turn | Not measured | 1476 | Only GPT-5.5 measured |
| LMArena Text: longer queries | Not measured | 1484 | Only GPT-5.5 measured |
| LMArena Text: writing and language | Not measured | 1466 | Only GPT-5.5 measured |
| LMArena Text: entertainment and media | Not measured | 1449 | Only GPT-5.5 measured |
| LMArena Vision: English | Not measured | 1292 | Only GPT-5.5 measured |
| LMArena Vision: Chinese | Not measured | 1360 | Only GPT-5.5 measured |
| LMArena Vision: reading text | Not measured | 1306 | Only GPT-5.5 measured |
| LMArena Vision: humor | Not measured | 1293 | Only GPT-5.5 measured |
| LMArena Vision: recognizing things | Not measured | 1231 | Only GPT-5.5 measured |
| LMArena Vision: creative writing | Not measured | 1301 | Only GPT-5.5 measured |
| LMArena Document | Not measured | 1486 | Only GPT-5.5 measured |
| Neither model has a result on the other 8 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3 Flash 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 Flash Preview costs less
Repository review
50K input + 3K output tokens
Gemini 3 Flash Preview costs less
Agent loop
200K input + 10K output tokens
Gemini 3 Flash 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 Flash Preview | OpenAI GPT-5.5 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | December 17, 2025 | April 24, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.50 | $5.00 |
| Output $/Mtok | $3.00 | $30.00 |
| Coding index | 75.8 | 67.8 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.37 | $1.65 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3 Flash Preview better than GPT-5.5 for coding?
Pick Gemini 3 Flash Preview for coding: it scores 75.8 on the Vibe Coding Index against 67.8 for GPT-5.5, though on 1 benchmark against 2. Pick GPT-5.5 when the context window is larger, 1.05M against 1.05M tokens, or when what matters is SWE-bench Verified (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, Gemini 3 Flash Preview or GPT-5.5?
Gemini 3 Flash Preview costs $0.50 per million input tokens and $3.00 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, Gemini 3 Flash Preview costs $0.37 and GPT-5.5 $1.65.
Which has the bigger context window, Gemini 3 Flash Preview or GPT-5.5?
GPT-5.5, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3 Flash Preview vs GPT-5.5 comparison based on?
58 benchmarks have a result for both models as of October 21, 2026. Gemini 3 Flash 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.