Gemini 2.5 Flash Lite vs GPT-4 Turbo
Gemini 2.5 Flash Lite leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 10.4 to 7.0, and Gemini 2.5 Flash Lite costs 75.0x less per output token ($0.40 vs $30.00 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
Gemini 2.5 Flash Lite or GPT-4 Turbo: 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 output tokens 75.0x cheaper ($0.40 vs $30.00 per million) and a larger context window (1.05M against 128K tokens).
- Shared results
- 9
- Gemini 2.5 Flash Lite only
- 21
- GPT-4 Turbo only
- 33
- Like-for-like categories
- 5 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 7.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 2.5 Flash Lite has a GPQA Diamond result, 70.2%.
Directional only
Math
AIME
No call
Only Gemini 2.5 Flash Lite has a AIME result, 42.1%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 2.5 Flash Lite has a MMLU Pro result, 79.1%.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite $0.0003, GPT-4 Turbo $0.025 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, GPT-4 Turbo not benchmarked.
- Widest category
- Coding, 30.2 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): Gemini 2.5 Flash Lite 59.3% against GPT-4 Turbo 29.1%, 30.2 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against GPT-4 Turbo $30.00 per million output tokens, 75.0x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-4 Turbo 128K.
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 Turbo | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 3 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 9 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 21.5 | Only GPT-4 Turbo measured |
| LiveCodeBench (Vals AI) | 71.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 29.1% | Gemini 2.5 Flash Lite |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LMArena Text: coding | Not measured | 1268 | Only GPT-4 Turbo measured |
| LMArena Text: software and IT | Not measured | 1267 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 7.0 | Gemini 2.5 Flash Lite |
| Epoch Capabilities Index | 133.8 | 127.3 | Gemini 2.5 Flash Lite |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 19.0% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMMU Pro (Vals AI) | 75.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 62.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 3.1% | Gemini 2.5 Flash Lite |
| LMArena Text: hard prompts | Not measured | 1251 | Only GPT-4 Turbo measured |
| LMArena Text: expert | Not measured | 1223 | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts in English | Not measured | 1266 | Only GPT-4 Turbo measured |
| Kagi LLM Benchmark | 40.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| AIME | 42.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MGSM (Vals AI) | 89.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| AA Math Index | 53.3 | Not measured | Only Gemini 2.5 Flash Lite measured |
| AIME 2025 (Artificial Analysis run) | 53.3% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LMArena Text: math | Not measured | 1272 | Only GPT-4 Turbo measured |
| LMArena Text: mathematical work | Not measured | 1268 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LegalBench (Vals AI) | 82.0% | 80.5% | Gemini 2.5 Flash Lite |
| CorpFin (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| TaxEval (Vals AI) | 66.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MortgageTax (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | 88.9% | 82.0% | 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% | 69.4% | Gemini 2.5 Flash Lite |
| MMLU | Not measured | 81.3% | Only GPT-4 Turbo measured |
| LMArena Text: science | Not measured | 1256 | Only GPT-4 Turbo measured |
| LMArena Text: medicine and healthcare | Not measured | 1239 | Only GPT-4 Turbo measured |
| LMArena Text: legal and government | Not measured | 1265 | Only GPT-4 Turbo measured |
| LMArena Text: business and finance | Not measured | 1222 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash Lite | GPT-4 Turbo | 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% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Long context reasoning (AA-LCR) | 55.7% | Not measured | Only Gemini 2.5 Flash Lite measured |
| DTBench | 62.8% | 61.6% | Gemini 2.5 Flash Lite |
| LMCA | 18.1% | 9.8% | Gemini 2.5 Flash Lite |
| LMArena Text | Not measured | 1272 | Only GPT-4 Turbo measured |
| LMArena Text: instruction following | Not measured | 1249 | Only GPT-4 Turbo measured |
| LMArena Text: creative writing | Not measured | 1268 | Only GPT-4 Turbo measured |
| LMArena Vision | Not measured | 1090 | Only GPT-4 Turbo measured |
| LMArena Text: English | Not measured | 1291 | Only GPT-4 Turbo measured |
| LMArena Text: non-English | Not measured | 1245 | Only GPT-4 Turbo measured |
| LMArena Text: Chinese | Not measured | 1242 | Only GPT-4 Turbo measured |
| LMArena Text: German | Not measured | 1259 | Only GPT-4 Turbo measured |
| LMArena Text: Japanese | Not measured | 1194 | Only GPT-4 Turbo measured |
| LMArena Text: Korean | Not measured | 1187 | Only GPT-4 Turbo measured |
| LMArena Text: French | Not measured | 1276 | Only GPT-4 Turbo measured |
| LMArena Text: Spanish | Not measured | 1260 | Only GPT-4 Turbo measured |
| LMArena Text: Russian | Not measured | 1259 | Only GPT-4 Turbo measured |
| LMArena Text: Polish | Not measured | 1302 | Only GPT-4 Turbo measured |
| LMArena Text: multi-turn | Not measured | 1267 | Only GPT-4 Turbo measured |
| LMArena Text: longer queries | Not measured | 1254 | Only GPT-4 Turbo measured |
| LMArena Text: writing and language | Not measured | 1279 | Only GPT-4 Turbo measured |
| LMArena Text: entertainment and media | Not measured | 1258 | Only GPT-4 Turbo measured |
| LMArena Vision: English | Not measured | 1097 | Only GPT-4 Turbo measured |
| LMArena Vision: Chinese | Not measured | 1045 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 20 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 Turbo | 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 2.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 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 2.5 Flash Lite | OpenAI GPT-4 Turbo |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 22, 2025 | April 9, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $0.10 | $10.00 |
| Output $/Mtok | $0.40 | $30.00 |
| 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 Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for output tokens 75.0x cheaper ($0.40 vs $30.00 per million) and a larger context window (1.05M against 128K tokens).
Which is cheaper, Gemini 2.5 Flash Lite or GPT-4 Turbo?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-4 Turbo costs $10.00 and $30.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-4 Turbo?
Gemini 2.5 Flash Lite, with 1.05M tokens against 128K.
How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-4 Turbo comparison based on?
9 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 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.