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Gemini 3.1 Flash Lite vs GPT-4o

Gemini 3.1 Flash Lite costs 6.7x less per output token than GPT-4o ($1.50 vs $10.00 per million). Updated October 21, 2026; 8 benchmarks have a result for both.

Gemini 3.1 Flash LiteGoogle
Coding
No data
Overall
No data
Output $/M
$1.50
8
GPT-4oOpenAI
Coding
No data
Overall
No data
Output $/M
$10.00
0
vs boards won of 8 shared

Gemini 3.1 Flash Lite or GPT-4o: which to pick

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

Pick Gemini 3.1 Flash Lite for output tokens 6.7x cheaper ($1.50 vs $10.00 per million) and a larger context window (1.05M against 128K tokens).

Shared results
8
Gemini 3.1 Flash Lite only
7
GPT-4o only
18
Like-for-like categories
4 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.

At a glance

Coding index
Gemini 3.1 Flash Lite not benchmarked, GPT-4o not benchmarked.
Widest category
General, 24.7 points apart on average over 4 shared benchmarks.
Widest single gap
IFBench: Gemini 3.1 Flash Lite 77.2% against GPT-4o 34.3%, 42.9 points apart on a 0 to 100 scale.
Output price
Gemini 3.1 Flash Lite $1.50 against GPT-4o $10.00 per million output tokens, 6.7x apart.
Context window
Gemini 3.1 Flash Lite takes 1.05M tokens, GPT-4o 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.

Boards won, where both have a result
CategoryGemini 3.1 Flash LiteBarsGPT-4oTies
Coding10
Agentic work10
Reasoning20
General40
All shared boards80
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
SWE-bench VerifiedNot measured38.8%Only GPT-4o measured
SWE-bench LiteNot measured38.0%Only GPT-4o measured
SWE-bench (full test set)Not measured18.8%Only GPT-4o measured
SWE-bench MultimodalNot measured30.4%Only GPT-4o measured
LiveCodeBench (Artificial Analysis run)Not measured30.9%Only GPT-4o measured
SciCode43.4%Not measuredOnly Gemini 3.1 Flash Lite measured
Terminal-Bench Hard (Artificial Analysis run)24.2%8.3%Gemini 3.1 Flash Lite
WeirdML52.2%Not measuredOnly Gemini 3.1 Flash Lite measured
Neither model has a result on the other 30 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
Epoch Capabilities Index144.3Not measuredOnly Gemini 3.1 Flash Lite measured
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
τ²-Bench Telecom31.3%25.1%Gemini 3.1 Flash Lite
GDPvalNot measured9.9%Only GPT-4o measured
DeepResearch Bench37.3%Not measuredOnly Gemini 3.1 Flash Lite measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
GPQA Diamond (Artificial Analysis run)82.2%54.3%Gemini 3.1 Flash Lite
Humanity's Last Exam (Artificial Analysis run)17.2%2.4%Gemini 3.1 Flash Lite
GPQA Diamond (Epoch AI run)81.8%Not measuredOnly Gemini 3.1 Flash Lite measured
ARC-AGINot measured4.5%Only GPT-4o measured
ARC-AGI-2Not measured0.0%Only GPT-4o measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
AA Math IndexNot measured6.0Only GPT-4o measured
AIME 2025 (Artificial Analysis run)Not measured6.0%Only GPT-4o measured
OTIS Mock AIME80.0%Not measuredOnly Gemini 3.1 Flash Lite measured
FrontierMath, tiers 1 to 327.7%Not measuredOnly Gemini 3.1 Flash Lite measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Knowledge benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
MMLU Pro (Artificial Analysis run)Not measured74.8%Only GPT-4o measured
MMLUNot measured88.1%Only GPT-4o measured
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
Design Arena: websitesNot measured831Only GPT-4o measured
Design Arena: UI componentsNot measured885Only GPT-4o measured
Design Arena: game devNot measured906Only GPT-4o measured
Design Arena: data vizNot measured858Only GPT-4o measured
Design Arena: 3DNot measured869Only GPT-4o measured
Design Arena: all code categoriesNot measured861Only GPT-4o measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
General benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
IFBench77.2%34.3%Gemini 3.1 Flash Lite
Long context reasoning (AA-LCR)74.3%49.3%Gemini 3.1 Flash Lite
DTBench76.8%64.5%Gemini 3.1 Flash Lite
LMCA35.0%16.6%Gemini 3.1 Flash Lite
Neither model has a result on the other 42 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.1 Flash Lite and GPT-4o
BenchmarkGemini 3.1 Flash LiteGPT-4oLeader
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 3.1 Flash Lite$0.0010Fits in one request
GPT-4o$0.0075Fits in one request

Gemini 3.1 Flash Lite costs less

Repository review

50K input + 3K output tokens

Gemini 3.1 Flash Lite$0.017Fits in one request
GPT-4o$0.155Fits in one request

Gemini 3.1 Flash Lite costs less

Agent loop

200K input + 10K output tokens

Gemini 3.1 Flash Lite$0.065Fits in one request
GPT-4o$0.600Exceeds the context window

Gemini 3.1 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 3.1 Flash Lite and GPT-4o
SpecificationGoogle Gemini 3.1 Flash LiteOpenAI GPT-4o
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedMay 7, 2026May 13, 2024
Context window1.05M128K
Input $/Mtok$0.25$2.50
Output $/Mtok$1.50$10.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.1 Flash Lite better than GPT-4o for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 3.1 Flash Lite for output tokens 6.7x cheaper ($1.50 vs $10.00 per million) and a larger context window (1.05M against 128K tokens).

Which is cheaper, Gemini 3.1 Flash Lite or GPT-4o?

Gemini 3.1 Flash Lite costs $0.25 per million input tokens and $1.50 per million output tokens; GPT-4o costs $2.50 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 3.1 Flash Lite or GPT-4o?

Gemini 3.1 Flash Lite, with 1.05M tokens against 128K.

How many benchmarks is the Gemini 3.1 Flash Lite vs GPT-4o comparison based on?

8 benchmarks have a result for both models as of October 21, 2026. Gemini 3.1 Flash Lite's coding index rests on 0 independent benchmarks and GPT-4o's on 0. Where only one model has a result, the page says so instead of naming a winner.

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