Gemini 3.5 Flash Lite vs GPT-5.5
GPT-5.5 leads Gemini 3.5 Flash Lite on coding, 71.3 to 49.0 on the Vibe Coding Index, and Gemini 3.5 Flash Lite costs 12.0x less per output token ($2.50 vs $30.00 per million). Updated October 22, 2026; 83 benchmarks have a result for both.
Gemini 3.5 Flash Lite or GPT-5.5: which to pick
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite.
Pick Gemini 3.5 Flash Lite for output tokens 12.0x cheaper ($2.50 vs $30.00 per million) and a lower cost per solved task ($0.41 against $1.65).
- Shared results
- 83
- Gemini 3.5 Flash Lite only
- 2
- GPT-5.5 only
- 51
- Like-for-like categories
- 7 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-5.5
GPT-5.5 scores 71.3 against 49.0.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 22.2.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.5
GPT-5.5 leads, 36.4 against 14.3.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 83.8%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 85.8%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.5 has a Design Arena: websites result, 1256.
Directional only
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 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.0015, GPT-5.5 $0.020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.41, GPT-5.5 $1.65.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.5 Flash Lite 49.0 from 3 benchmarks, GPT-5.5 71.3 from 5 benchmarks.
- Widest category
- Math, 33.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- ARC-AGI-2: Gemini 3.5 Flash Lite 10.3% against GPT-5.5 85.0%, 74.7 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash Lite $2.50 against GPT-5.5 $30.00 per million output tokens, 12.0x apart.
- Context window
- Gemini 3.5 Flash Lite 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 3.5 Flash Lite | Bars | GPT-5.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 15 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 6 | ||
| Reasoning | 0 | 14 | ||
| Math | 0 | 6 | ||
| Knowledge | 0 | 11 | ||
| General | 0 | 29 | ||
| All shared boards | 0 | 83 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index015
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 85.1% | Only GPT-5.5 measured |
| LMArena WebDev | 1435 | 1513 | GPT-5.5 |
| AA Coding Index | 49.3 | 74.9 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 79.0% | 85.3% | GPT-5.5 |
| SWE-bench Verified (Vals AI) | 75.0% | 82.6% | GPT-5.5 |
| Vibe Code Bench (Vals AI) | 37.2% | 69.8% | GPT-5.5 |
| Code migration (Vals AI) | 6.2% | 45.2% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.0% | 0.5% | GPT-5.5 |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 76.4% | GPT-5.5 |
| SkillsBench (Vals AI) | Not measured | 62.5% | Only GPT-5.5 measured |
| CyberBench (Vals AI) | 59.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 41.3% | 56.1% | GPT-5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 60.6% | Only GPT-5.5 measured |
| Terminal-Bench | Not measured | 84.7% | Only GPT-5.5 measured |
| FrontierCode | Not measured | 43.0% | Only GPT-5.5 measured |
| GSO-Bench | Not measured | 40.2% | Only GPT-5.5 measured |
| WeirdML | 39.0% | 84.9% | GPT-5.5 |
| MirrorCode | Not measured | 10.0% | Only GPT-5.5 measured |
| ALE-Bench | 765.3 | 1943.0 | GPT-5.5 |
| LMArena Text: coding | 1453 | 1494 | GPT-5.5 |
| LMArena Text: software and IT | 1451 | 1493 | GPT-5.5 |
| LMArena WebDev: React | 1408 | 1506 | GPT-5.5 |
| LMArena WebDev: HTML | Not measured | 1543 | Only GPT-5.5 measured |
| LMArena WebDev: from an image | 1448 | 1532 | GPT-5.5 |
| SciCode | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| 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 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.2 | 38.4 | GPT-5.5 |
| Epoch Capabilities Index | 144.9 | 159.7 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 14.3 | 36.4 | GPT-5.5 |
| Design Arena: agents building web apps | Not measured | 1117 | Only GPT-5.5 measured |
| Design Arena: agents building full-stack apps | Not measured | 1089 | Only GPT-5.5 measured |
| Design Arena: agents building mobile apps | Not measured | 1142 | Only GPT-5.5 measured |
| Design Arena: agents building Android apps | Not measured | 1164 | Only GPT-5.5 measured |
| Design Arena: agents building Godot games | Not measured | 1173 | Only GPT-5.5 measured |
| Design Arena: agents building games | Not measured | 1179 | Only GPT-5.5 measured |
| Design Arena: HTML slides | Not measured | 1017 | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | Not measured | 1084 | Only GPT-5.5 measured |
| 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) | 47.4% | 51.8% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 7.2% | 21.8% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 13.9% | 40.4% | GPT-5.5 |
| Excel Modeling Benchmark (Vals AI) | 43.2% | 64.5% | GPT-5.5 |
| Time Horizon Index (Vals AI) | Not measured | 8.3% | Only GPT-5.5 measured |
| τ²-Bench Telecom | Not measured | 93.9% | Only GPT-5.5 measured |
| APEX-Agents | 29.3% | 55.1% | GPT-5.5 |
| Remote Labor Index | Not measured | 6.3% | Only GPT-5.5 measured |
| OSWorld 2.0 | Not measured | 13.0% | Only GPT-5.5 measured |
| DeepResearch Bench | Not measured | 54.0% | Only GPT-5.5 measured |
| PostTrainBench | Not measured | 27.2% | Only GPT-5.5 measured |
| Vending-Bench 2 | Not measured | $7,524 | Only GPT-5.5 measured |
| Neither model has a result on the other 16 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index014
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.8% | 93.2% | GPT-5.5 |
| LiveBench reasoning | Not measured | 89.7% | Only GPT-5.5 measured |
| MMMU Pro (Vals AI) | 83.6% | 88.3% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 83.8% | 93.5% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 18.8% | 45.8% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 83.3% | 90.7% | GPT-5.5 |
| ARC-AGI | 53.5% | 95.0% | GPT-5.5 |
| ARC-AGI-2 | 10.3% | 85.0% | GPT-5.5 |
| SimpleBench | Not measured | 69.0% | Only GPT-5.5 measured |
| Chess puzzles | 21.0% | 63.0% | GPT-5.5 |
| Mystery game puzzles | 19.0% | 56.0% | GPT-5.5 |
| EBR-bench | Not measured | 34.3% | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1441 | 1489 | GPT-5.5 |
| LMArena Text: expert | 1434 | 1507 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1440 | 1483 | GPT-5.5 |
| LMArena Vision: diagrams | 1284 | 1325 | GPT-5.5 |
| LMArena Vision: homework | 1291 | 1332 | GPT-5.5 |
| Kagi LLM Benchmark | Not measured | 88.8% | Only GPT-5.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | 84.4% | GPT-5.5 |
| FrontierMath, tiers 1 to 3 | 26.0% | 85.3% | GPT-5.5 |
| FrontierMath, tier 4 | 0.0% | 72.5% | GPT-5.5 |
| ProofBench | 13.0% | 50.0% | GPT-5.5 |
| LMArena Text: math | 1434 | 1487 | GPT-5.5 |
| LMArena Text: mathematical work | 1433 | 1496 | GPT-5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| MMLU Pro | 85.8% | 88.1% | GPT-5.5 |
| LegalBench (Vals AI) | 84.1% | 86.5% | GPT-5.5 |
| CaseLaw (Vals AI) | Not measured | 66.2% | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 60.7% | 68.4% | GPT-5.5 |
| TaxEval (Vals AI) | 72.6% | 75.0% | GPT-5.5 |
| MortgageTax (Vals AI) | 68.7% | 68.8% | GPT-5.5 |
| MedCode (Vals AI) | 43.5% | 49.1% | GPT-5.5 |
| SimpleQA Verified | Not measured | 63.0% | Only GPT-5.5 measured |
| LMArena Text: science | 1451 | 1485 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1438 | 1465 | GPT-5.5 |
| LMArena Text: legal and government | 1431 | 1491 | GPT-5.5 |
| LMArena Text: business and finance | 1423 | 1478 | GPT-5.5 |
| FACTS Benchmark Suite | 53.5% | 66.7% | GPT-5.5 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1256 | Only GPT-5.5 measured |
| Design Arena: UI components | Not measured | 1257 | Only GPT-5.5 measured |
| Design Arena: game dev | Not measured | 1293 | Only GPT-5.5 measured |
| Design Arena: data viz | Not measured | 1264 | Only GPT-5.5 measured |
| Design Arena: 3D | Not measured | 1197 | Only GPT-5.5 measured |
| Design Arena: all code categories | Not measured | 1260 | Only GPT-5.5 measured |
| Design Arena: SVG | Not measured | 1234 | Only GPT-5.5 measured |
| Design Arena: ASCII art | Not measured | 1255 | 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 index029
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.6% | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | 51.8% | 60.9% | GPT-5.5 |
| SAGE (Vals AI) | 47.3% | 51.5% | GPT-5.5 |
| MedScribe (Vals AI) | 70.9% | 86.9% | GPT-5.5 |
| Vals Multimodal Index | Not measured | 68.1% | Only GPT-5.5 measured |
| IFBench | Not measured | 75.9% | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 76.0% | 84.3% | GPT-5.5 |
| DTBench | 83.5% | 96.0% | GPT-5.5 |
| LMCA | 37.6% | 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 | 1435 | 1471 | GPT-5.5 |
| LMArena Text: instruction following | 1419 | 1478 | GPT-5.5 |
| LMArena Text: creative writing | 1421 | 1455 | GPT-5.5 |
| LMArena Vision | 1269 | 1297 | GPT-5.5 |
| LMArena Text: English | 1438 | 1470 | GPT-5.5 |
| LMArena Text: non-English | 1427 | 1467 | GPT-5.5 |
| LMArena Text: Chinese | 1468 | 1534 | GPT-5.5 |
| LMArena Text: German | 1454 | 1480 | GPT-5.5 |
| LMArena Text: Japanese | 1426 | 1499 | GPT-5.5 |
| LMArena Text: Korean | 1407 | 1460 | GPT-5.5 |
| LMArena Text: French | 1451 | 1485 | GPT-5.5 |
| LMArena Text: Spanish | 1441 | 1468 | GPT-5.5 |
| LMArena Text: Russian | 1443 | 1473 | GPT-5.5 |
| LMArena Text: Polish | 1437 | 1465 | GPT-5.5 |
| LMArena Text: multi-turn | 1445 | 1476 | GPT-5.5 |
| LMArena Text: longer queries | 1435 | 1484 | GPT-5.5 |
| LMArena Text: writing and language | 1428 | 1466 | GPT-5.5 |
| LMArena Text: entertainment and media | 1414 | 1449 | GPT-5.5 |
| LMArena Vision: English | 1269 | 1292 | GPT-5.5 |
| LMArena Vision: Chinese | 1311 | 1360 | GPT-5.5 |
| LMArena Vision: reading text | 1280 | 1306 | GPT-5.5 |
| LMArena Vision: humor | 1287 | 1293 | GPT-5.5 |
| LMArena Vision: recognizing things | Not measured | 1231 | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1260 | 1301 | GPT-5.5 |
| 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 3.5 Flash Lite | 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 3.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash Lite 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 3.5 Flash Lite | OpenAI GPT-5.5 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 21, 2026 | April 24, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $5.00 |
| Output $/Mtok | $2.50 | $30.00 |
| Coding index | 49.0 | 71.3 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | $0.41 | $1.65 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash Lite better than GPT-5.5 for coding?
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite. Pick Gemini 3.5 Flash Lite for output tokens 12.0x cheaper ($2.50 vs $30.00 per million) and a lower cost per solved task ($0.41 against $1.65).
Which is cheaper, Gemini 3.5 Flash Lite or GPT-5.5?
Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, Gemini 3.5 Flash Lite costs $0.41 and GPT-5.5 $1.65.
Which has the bigger context window, Gemini 3.5 Flash Lite or GPT-5.5?
GPT-5.5, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3.5 Flash Lite vs GPT-5.5 comparison based on?
83 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash Lite's coding index rests on 3 independent benchmarks and GPT-5.5's on 5. Where only one model has a result, the page says so instead of naming a winner.