Gemini 2.5 Flash Lite vs GPT-4.1 Nano
Gemini 2.5 Flash Lite leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 10.4 to 7.8, at about the same output price ($0.40 vs $0.40 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
Gemini 2.5 Flash Lite or GPT-4.1 Nano: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash Lite for a larger context window (1.05M against 1.05M tokens).
- Shared results
- 27
- Gemini 2.5 Flash Lite only
- 3
- GPT-4.1 Nano only
- 44
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 10.4 against 7.8.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 70.2% against 50.8%.
Same board, both measured
Math
AIME
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 42.1% against 26.5%.
Same board, both measured
Knowledge
MMLU Pro
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 79.1% against 63.5%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-4.1 Nano has a Design Arena: websites result, 972.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
Gemini 2.5 Flash Lite $0.0003, GPT-4.1 Nano $0.0003 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, GPT-4.1 Nano not benchmarked.
- Widest category
- Math, 23.6 points apart on average over 4 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Gemini 2.5 Flash Lite 55.7% against GPT-4.1 Nano 20.3%, 35.3 points apart on a 0 to 100 scale.
- Output price
- Both cost $0.40 per million output tokens.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-4.1 Nano 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 2.5 Flash Lite | Bars | GPT-4.1 Nano | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 7 | 0 | ||
| General | 4 | 0 | ||
| All shared boards | 27 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 8.9% | Only GPT-4.1 Nano measured |
| AA Coding Index | Not measured | 11.1 | Only GPT-4.1 Nano measured |
| LiveCodeBench (Vals AI) | 71.4% | 42.7% | Gemini 2.5 Flash Lite |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 32.6% | Gemini 2.5 Flash Lite |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 3.8% | Gemini 2.5 Flash Lite |
| WeirdML | Not measured | 19.0% | Only GPT-4.1 Nano measured |
| LMArena Text: coding | Not measured | 1306 | Only GPT-4.1 Nano measured |
| LMArena Text: software and IT | Not measured | 1305 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 7.8 | Gemini 2.5 Flash Lite |
| Epoch Capabilities Index | 133.8 | 129.5 | Gemini 2.5 Flash Lite |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 19.0% | 17.3% | Gemini 2.5 Flash Lite |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | 33.1% | Gemini 2.5 Flash Lite |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | 50.8% | Gemini 2.5 Flash Lite |
| MMMU Pro (Vals AI) | 75.4% | 55.0% | Gemini 2.5 Flash Lite |
| GPQA Diamond (Artificial Analysis run) | 62.5% | 51.2% | Gemini 2.5 Flash Lite |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 3.8% | Gemini 2.5 Flash Lite |
| GPQA Diamond (Epoch AI run) | Not measured | 48.9% | Only GPT-4.1 Nano measured |
| ARC-AGI | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| Chess puzzles | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts | Not measured | 1286 | Only GPT-4.1 Nano measured |
| LMArena Text: expert | Not measured | 1271 | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts in English | Not measured | 1293 | Only GPT-4.1 Nano measured |
| Kagi LLM Benchmark | 40.5% | 33.3% | Gemini 2.5 Flash Lite |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AIME | 42.1% | 26.5% | Gemini 2.5 Flash Lite |
| MATH 500 (Vals AI) | Not measured | 80.2% | Only GPT-4.1 Nano measured |
| MGSM (Vals AI) | 89.5% | 69.3% | Gemini 2.5 Flash Lite |
| AA Math Index | 53.3 | 24.0 | Gemini 2.5 Flash Lite |
| AIME 2025 (Artificial Analysis run) | 53.3% | 24.0% | Gemini 2.5 Flash Lite |
| OTIS Mock AIME | Not measured | 28.9% | Only GPT-4.1 Nano measured |
| MATH level 5 | Not measured | 70.0% | Only GPT-4.1 Nano measured |
| LMArena Text: math | Not measured | 1274 | Only GPT-4.1 Nano measured |
| LMArena Text: mathematical work | Not measured | 1274 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | 63.5% | Gemini 2.5 Flash Lite |
| LegalBench (Vals AI) | 82.0% | 61.1% | Gemini 2.5 Flash Lite |
| CorpFin (Vals AI) | 57.6% | 42.1% | Gemini 2.5 Flash Lite |
| TaxEval (Vals AI) | 66.2% | 60.8% | Gemini 2.5 Flash Lite |
| MortgageTax (Vals AI) | 57.6% | 52.8% | Gemini 2.5 Flash Lite |
| MedQA (Vals AI) | 88.9% | 68.2% | Gemini 2.5 Flash Lite |
| MedCode (Vals AI) | 34.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMLU Pro (Artificial Analysis run) | 75.9% | 65.7% | Gemini 2.5 Flash Lite |
| SimpleQA Verified | Not measured | 6.0% | Only GPT-4.1 Nano measured |
| LMArena Text: science | Not measured | 1297 | Only GPT-4.1 Nano measured |
| LMArena Text: medicine and healthcare | Not measured | 1276 | Only GPT-4.1 Nano measured |
| LMArena Text: legal and government | Not measured | 1300 | Only GPT-4.1 Nano measured |
| LMArena Text: business and finance | Not measured | 1267 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 972 | Only GPT-4.1 Nano measured |
| Design Arena: UI components | Not measured | 913 | Only GPT-4.1 Nano measured |
| Design Arena: game dev | Not measured | 970 | Only GPT-4.1 Nano measured |
| Design Arena: data viz | Not measured | 891 | Only GPT-4.1 Nano measured |
| Design Arena: 3D | Not measured | 924 | Only GPT-4.1 Nano measured |
| Design Arena: all code categories | Not measured | 962 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 30.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedScribe (Vals AI) | 75.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| IFBench | 49.9% | 32.0% | Gemini 2.5 Flash Lite |
| Long context reasoning (AA-LCR) | 55.7% | 20.3% | Gemini 2.5 Flash Lite |
| DTBench | 62.8% | 52.5% | Gemini 2.5 Flash Lite |
| LMCA | 18.1% | 5.5% | Gemini 2.5 Flash Lite |
| Fiction.LiveBench | Not measured | 25.0% | Only GPT-4.1 Nano measured |
| LMArena Text | Not measured | 1285 | Only GPT-4.1 Nano measured |
| LMArena Text: instruction following | Not measured | 1266 | Only GPT-4.1 Nano measured |
| LMArena Text: creative writing | Not measured | 1260 | Only GPT-4.1 Nano measured |
| LMArena Vision | Not measured | 1063 | Only GPT-4.1 Nano measured |
| LMArena Text: English | Not measured | 1303 | Only GPT-4.1 Nano measured |
| LMArena Text: non-English | Not measured | 1260 | Only GPT-4.1 Nano measured |
| LMArena Text: Chinese | Not measured | 1270 | Only GPT-4.1 Nano measured |
| LMArena Text: German | Not measured | 1288 | Only GPT-4.1 Nano measured |
| LMArena Text: Japanese | Not measured | 1198 | Only GPT-4.1 Nano measured |
| LMArena Text: Russian | Not measured | 1261 | Only GPT-4.1 Nano measured |
| LMArena Text: multi-turn | Not measured | 1277 | Only GPT-4.1 Nano measured |
| LMArena Text: longer queries | Not measured | 1283 | Only GPT-4.1 Nano measured |
| LMArena Text: writing and language | Not measured | 1261 | Only GPT-4.1 Nano measured |
| LMArena Text: entertainment and media | Not measured | 1243 | Only GPT-4.1 Nano measured |
| LMArena Vision: English | Not measured | 1101 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-4.1 Nano | 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 Flash Lite | OpenAI GPT-4.1 Nano |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 22, 2025 | April 14, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.10 | $0.10 |
| Output $/Mtok | $0.40 | $0.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash Lite better than GPT-4.1 Nano for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for a larger context window (1.05M against 1.05M tokens).
Which is cheaper, Gemini 2.5 Flash Lite or GPT-4.1 Nano?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-4.1 Nano?
Gemini 2.5 Flash Lite, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-4.1 Nano comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash Lite's coding index rests on 0 independent benchmarks and GPT-4.1 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.