Gemini 2.5 Flash Lite vs GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads Gemini 2.5 Flash Lite on the Artificial Analysis Intelligence Index, 20.4 to 10.4, and Gemini 2.5 Flash Lite costs 5.0x less per output token ($0.40 vs $2.00 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
Gemini 2.5 Flash Lite or GPT-5.1-Codex-Mini: 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 5.0x cheaper ($0.40 vs $2.00 per million) and a larger context window (1.05M against 400K tokens).
- Shared results
- 11
- Gemini 2.5 Flash Lite only
- 17
- GPT-5.1-Codex-Mini only
- 11
- 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
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 20.4 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-5.1-Codex-Mini has a Design Arena: websites result, 1111.
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-5.1-Codex-Mini $0.0013 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, GPT-5.1-Codex-Mini not benchmarked.
- Widest category
- Agentic work, 43.9 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Flash Lite 19.0% against GPT-5.1-Codex-Mini 62.9%, 43.9 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against GPT-5.1-Codex-Mini $2.00 per million output tokens, 5.0x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-5.1-Codex-Mini 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-5.1-Codex-Mini | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1244 | Only GPT-5.1-Codex-Mini measured |
| LiveCodeBench (Vals AI) | 71.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 83.6% | GPT-5.1-Codex-Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 33.3% | GPT-5.1-Codex-Mini |
| Terminal-Bench | Not measured | 61.6% | Only GPT-5.1-Codex-Mini measured |
| LMArena WebDev: HTML | Not measured | 1253 | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 20.4 | GPT-5.1-Codex-Mini |
| Epoch Capabilities Index | 133.8 | Not measured | Only Gemini 2.5 Flash Lite measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 19.0% | 62.9% | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | 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% | 81.3% | GPT-5.1-Codex-Mini |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 18.5% | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | 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 | 91.7 | GPT-5.1-Codex-Mini |
| AIME 2025 (Artificial Analysis run) | 53.3% | 91.7% | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | GPT-5.1-Codex-Mini | 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% | 82.0% | GPT-5.1-Codex-Mini |
| 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-5.1-Codex-Mini | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1111 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: UI components | Not measured | 1081 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: game dev | Not measured | 1092 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: data viz | Not measured | 1097 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: 3D | Not measured | 988 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: all code categories | Not measured | 1094 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: SVG | Not measured | 978 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | Not measured | 1105 | Only GPT-5.1-Codex-Mini 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-5.1-Codex-Mini | 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% | 67.9% | GPT-5.1-Codex-Mini |
| Long context reasoning (AA-LCR) | 55.7% | 66.7% | GPT-5.1-Codex-Mini |
| 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-5.1-Codex-Mini | 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-5.1-Codex-Mini |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 22, 2025 | November 13, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.10 | $0.25 |
| Output $/Mtok | $0.40 | $2.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash Lite better than GPT-5.1-Codex-Mini 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 5.0x cheaper ($0.40 vs $2.00 per million) and a larger context window (1.05M against 400K tokens).
Which is cheaper, Gemini 2.5 Flash Lite or GPT-5.1-Codex-Mini?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.1-Codex-Mini costs $0.25 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-5.1-Codex-Mini?
Gemini 2.5 Flash Lite, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-5.1-Codex-Mini comparison based on?
11 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-5.1-Codex-Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.