Gemini 2.5 Flash Lite vs GPT-5.3-Codex
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only GPT-5.3-Codex has a coding score, 60.0 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding.
Gemini 2.5 Flash Lite has the edge where output tokens cost 35.0x less, and where the context window is larger, 1.05M against 400K tokens.
- Shared results
- 9
- Gemini 2.5 Flash Lite only
- 19
- GPT-5.3-Codex only
- 25
- Like-for-like categories
- 5 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GPT-5.3-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.3-Codex
GPT-5.3-Codex leads, 32.5 against 10.4.
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
Web design
Design Arena: websites
No call
Only GPT-5.3-Codex has a Design Arena: websites result, 1163.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite $0.0003, GPT-5.3-Codex $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.3-Codex has the number, $0.59.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, GPT-5.3-Codex 60.0 from 3 benchmarks.
- Widest category
- Agentic work, 67.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Flash Lite 19.0% against GPT-5.3-Codex 86.0%, 67.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against GPT-5.3-Codex $14.00 per million output tokens, 35.0x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-5.3-Codex 400K.
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-5.3-Codex | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 9 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1407 | Only GPT-5.3-Codex measured |
| LiveCodeBench (Vals AI) | 71.4% | 87.3% | GPT-5.3-Codex |
| SWE-bench Verified (Vals AI) | Not measured | 78.0% | Only GPT-5.3-Codex measured |
| Vibe Code Bench (Vals AI) | Not measured | 61.8% | Only GPT-5.3-Codex measured |
| IOI (Vals AI) | Not measured | 53.8% | Only GPT-5.3-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 53.0% | GPT-5.3-Codex |
| Terminal-Bench | Not measured | 78.4% | Only GPT-5.3-Codex measured |
| WeirdML | Not measured | 79.3% | Only GPT-5.3-Codex measured |
| ALE-Bench | Not measured | 1655.2 | Only GPT-5.3-Codex measured |
| LMArena WebDev: React | Not measured | 1395 | Only GPT-5.3-Codex measured |
| LMArena WebDev: HTML | Not measured | 1422 | Only GPT-5.3-Codex measured |
| LMArena WebDev: from an image | Not measured | 1443 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 32.5 | GPT-5.3-Codex |
| Epoch Capabilities Index | 133.8 | 157.1 | GPT-5.3-Codex |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1032 | Only GPT-5.3-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 983 | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1053 | Only GPT-5.3-Codex measured |
| Design Arena: agents building Android apps | Not measured | 1084 | Only GPT-5.3-Codex measured |
| Design Arena: agents building Godot games | Not measured | 1124 | Only GPT-5.3-Codex measured |
| τ²-Bench Telecom | 19.0% | 86.0% | GPT-5.3-Codex |
| METR time horizons | Not measured | 74.5% | Only GPT-5.3-Codex measured |
| Vending-Bench 2 | Not measured | $5,940 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | 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% | 91.5% | GPT-5.3-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 42.5% | GPT-5.3-Codex |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | 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 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LegalBench (Vals AI) | 82.0% | Not measured | Only Gemini 2.5 Flash Lite measured |
| 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% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedCode (Vals AI) | 34.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMLU Pro (Artificial Analysis run) | 75.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1163 | Only GPT-5.3-Codex measured |
| Design Arena: UI components | Not measured | 1137 | Only GPT-5.3-Codex measured |
| Design Arena: game dev | Not measured | 1161 | Only GPT-5.3-Codex measured |
| Design Arena: data viz | Not measured | 1163 | Only GPT-5.3-Codex measured |
| Design Arena: 3D | Not measured | 1008 | Only GPT-5.3-Codex measured |
| Design Arena: all code categories | Not measured | 1145 | Only GPT-5.3-Codex measured |
| Design Arena: SVG | Not measured | 1129 | Only GPT-5.3-Codex measured |
| Design Arena: ASCII art | Not measured | 1151 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | 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% | 75.4% | GPT-5.3-Codex |
| Long context reasoning (AA-LCR) | 55.7% | 83.3% | GPT-5.3-Codex |
| DTBench | 62.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LMCA | 18.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 40 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.3-Codex | 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-5.3-Codex |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 22, 2025 | February 24, 2026 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.10 | $1.75 |
| Output $/Mtok | $0.40 | $14.00 |
| Coding index | Not benchmarked | 60.0 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash Lite better than GPT-5.3-Codex for coding?
Only GPT-5.3-Codex has a coding score, 60.0 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding. Gemini 2.5 Flash Lite has the edge where output tokens cost 35.0x less, and where the context window is larger, 1.05M against 400K tokens.
Which is cheaper, Gemini 2.5 Flash Lite or GPT-5.3-Codex?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.3-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.3-Codex only.
Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-5.3-Codex?
Gemini 2.5 Flash Lite, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-5.3-Codex comparison based on?
9 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-5.3-Codex's on 3. Where only one model has a result, the page says so instead of naming a winner.