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Gemini 2.5 Flash Lite vs GPT-4

Updated October 21, 2026. 7 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemini 2.5 Flash LiteGoogle
Coding
No data
Overall
10.4
Output $/M
$0.40
7
GPT-4OpenAI
Coding
No data
Overall
6.7
Output $/M
$60.00
0
vs boards won of 7 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Gemini 2.5 Flash Lite has the edge where output tokens cost 150.0x less, and where the context window is larger, 1.05M against 8K tokens.

Shared results
7
Gemini 2.5 Flash Lite only
21
GPT-4 only
38
Like-for-like categories
4 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.

At a glance

Coding index
Gemini 2.5 Flash Lite not benchmarked, GPT-4 not benchmarked.
Widest category
Reasoning, 27.6 points apart on average over 1 shared benchmark.
Widest single gap
GPQA Diamond (Artificial Analysis run): Gemini 2.5 Flash Lite 62.5% against GPT-4 34.9%, 27.6 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash Lite $0.40 against GPT-4 $60.00 per million output tokens, 150.0x apart.
Context window
Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-4 8K.

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.

Boards won, where both have a result
CategoryGemini 2.5 Flash LiteBarsGPT-4Ties
Intelligence20
Reasoning10
Knowledge10
General30
All shared boards70
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
Coding benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
SWE-bench VerifiedNot measured22.4%Only GPT-4 measured
SWE-bench LiteNot measured39.7%Only GPT-4 measured
SWE-bench (full test set)Not measured12.5%Only GPT-4 measured
AA Coding IndexNot measured13.1Only GPT-4 measured
LiveCodeBench (Vals AI)71.4%Not measuredOnly Gemini 2.5 Flash Lite measured
LiveCodeBench (Artificial Analysis run)59.3%Not measuredOnly Gemini 2.5 Flash Lite measured
Terminal-Bench Hard (Artificial Analysis run)4.5%Not measuredOnly Gemini 2.5 Flash Lite measured
LMArena Text: codingNot measured1209Only GPT-4 measured
LMArena Text: software and ITNot measured1195Only GPT-4 measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
AA Intelligence Index10.46.7Gemini 2.5 Flash Lite
Epoch Capabilities Index133.8125.7Gemini 2.5 Flash Lite
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
τ²-Bench Telecom19.0%Not measuredOnly Gemini 2.5 Flash Lite measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
GPQA Diamond70.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MMMU Pro (Vals AI)75.4%Not measuredOnly Gemini 2.5 Flash Lite measured
GPQA Diamond (Artificial Analysis run)62.5%34.9%Gemini 2.5 Flash Lite
Humanity's Last Exam (Artificial Analysis run)6.8%Not measuredOnly Gemini 2.5 Flash Lite measured
BIG-Bench HardNot measured75.1%Only GPT-4 measured
LMArena Text: hard promptsNot measured1200Only GPT-4 measured
LMArena Text: expertNot measured1149Only GPT-4 measured
LMArena Text: hard prompts in EnglishNot measured1209Only GPT-4 measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
AIME42.1%Not measuredOnly Gemini 2.5 Flash Lite measured
MGSM (Vals AI)89.5%Not measuredOnly Gemini 2.5 Flash Lite measured
AA Math Index53.3Not measuredOnly Gemini 2.5 Flash Lite measured
AIME 2025 (Artificial Analysis run)53.3%Not measuredOnly Gemini 2.5 Flash Lite measured
GSM8KNot measured92.0%Only GPT-4 measured
LMArena Text: mathNot measured1230Only GPT-4 measured
LMArena Text: mathematical workNot measured1228Only GPT-4 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
MMLU Pro79.1%Not measuredOnly Gemini 2.5 Flash Lite measured
LegalBench (Vals AI)82.0%Not measuredOnly Gemini 2.5 Flash Lite measured
CorpFin (Vals AI)57.6%Not measuredOnly Gemini 2.5 Flash Lite measured
TaxEval (Vals AI)66.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MortgageTax (Vals AI)57.6%Not measuredOnly Gemini 2.5 Flash Lite measured
MedQA (Vals AI)88.9%Not measuredOnly Gemini 2.5 Flash Lite measured
MedCode (Vals AI)34.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MMLU Pro (Artificial Analysis run)75.9%56.2%Gemini 2.5 Flash Lite
MMLUNot measured86.4%Only GPT-4 measured
AI2 Reasoning ChallengeNot measured96.3%Only GPT-4 measured
LMArena Text: scienceNot measured1177Only GPT-4 measured
LMArena Text: medicine and healthcareNot measured1145Only GPT-4 measured
LMArena Text: legal and governmentNot measured1191Only GPT-4 measured
LMArena Text: business and financeNot measured1145Only GPT-4 measured
Neither model has a result on the other 3 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
General benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
SAGE (Vals AI)30.8%Not measuredOnly Gemini 2.5 Flash Lite measured
MedScribe (Vals AI)75.8%Not measuredOnly Gemini 2.5 Flash Lite measured
IFBench49.9%33.2%Gemini 2.5 Flash Lite
Long context reasoning (AA-LCR)55.7%Not measuredOnly Gemini 2.5 Flash Lite measured
DTBench62.8%62.7%Gemini 2.5 Flash Lite
LMCA18.1%17.1%Gemini 2.5 Flash Lite
HellaSwagNot measured95.3%Only GPT-4 measured
WinoGrandeNot measured87.5%Only GPT-4 measured
LMArena TextNot measured1206Only GPT-4 measured
LMArena Text: instruction followingNot measured1201Only GPT-4 measured
LMArena Text: creative writingNot measured1191Only GPT-4 measured
LMArena Text: EnglishNot measured1220Only GPT-4 measured
LMArena Text: non-EnglishNot measured1194Only GPT-4 measured
LMArena Text: ChineseNot measured1184Only GPT-4 measured
LMArena Text: GermanNot measured1198Only GPT-4 measured
LMArena Text: JapaneseNot measured1137Only GPT-4 measured
LMArena Text: KoreanNot measured1087Only GPT-4 measured
LMArena Text: FrenchNot measured1220Only GPT-4 measured
LMArena Text: SpanishNot measured1197Only GPT-4 measured
LMArena Text: RussianNot measured1195Only GPT-4 measured
LMArena Text: PolishNot measured1265Only GPT-4 measured
LMArena Text: multi-turnNot measured1206Only GPT-4 measured
LMArena Text: longer queriesNot measured1190Only GPT-4 measured
LMArena Text: writing and languageNot measured1219Only GPT-4 measured
LMArena Text: entertainment and mediaNot measured1184Only GPT-4 measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash Lite and GPT-4
BenchmarkGemini 2.5 Flash LiteGPT-4Leader
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$0.0003Fits in one request
GPT-4$0.060Fits in one request

Gemini 2.5 Flash Lite costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash Lite$0.0062Fits in one request
GPT-4$1.68Exceeds the context window

Gemini 2.5 Flash Lite costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash Lite$0.024Fits in one request
GPT-4$6.60Exceeds the context window

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.

Specifications of Gemini 2.5 Flash Lite and GPT-4
SpecificationGoogle Gemini 2.5 Flash LiteOpenAI GPT-4
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 22, 2025May 28, 2023
Context window1.05M8K
Input $/Mtok$0.10$30.00
Output $/Mtok$0.40$60.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash Lite better than GPT-4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Gemini 2.5 Flash Lite has the edge where output tokens cost 150.0x less, and where the context window is larger, 1.05M against 8K tokens.

Which is cheaper, Gemini 2.5 Flash Lite or GPT-4?

Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-4 costs $30.00 and $60.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-4?

Gemini 2.5 Flash Lite, with 1.05M tokens against 8K.

How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-4 comparison based on?

7 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash Lite's coding index rests on 0 independent benchmarks and GPT-4's on 0. Where only one model has a result, the page says so instead of naming a winner.

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