Gemini 3.5 Flash Lite vs GPT-5.2-Codex
Gemini 3.5 Flash Lite leads GPT-5.2-Codex on coding, 49.0 to 45.4 on the Vibe Coding Index, and Gemini 3.5 Flash Lite costs 5.6x less per output token ($2.50 vs $14.00 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
Gemini 3.5 Flash Lite or GPT-5.2-Codex: which to pick
Pick Gemini 3.5 Flash Lite for coding: it scores 49.0 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex.
Pick GPT-5.2-Codex for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 10
- Gemini 3.5 Flash Lite only
- 75
- GPT-5.2-Codex only
- 12
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite scores 49.0 against 45.4.
3 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.2-Codex
GPT-5.2-Codex leads, 28.5 against 22.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 3.5 Flash Lite has a AA Agentic Index result, 14.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash Lite has a GPQA Diamond result, 83.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash Lite has a MMLU Pro result, 85.8%.
Directional only
Long documents
Listed context window
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.0015, GPT-5.2-Codex $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.41, GPT-5.2-Codex $0.43.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.5 Flash Lite 49.0 from 3 benchmarks, GPT-5.2-Codex 45.4 from 3 benchmarks.
- Widest category
- Reasoning, 11.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- ALE-Bench: Gemini 3.5 Flash Lite 765.3 against GPT-5.2-Codex 1299.9, 17.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash Lite $2.50 against GPT-5.2-Codex $14.00 per million output tokens, 5.6x apart.
- Context window
- Gemini 3.5 Flash Lite takes 1.05M tokens, GPT-5.2-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 3.5 Flash Lite | Bars | GPT-5.2-Codex | Ties |
|---|---|---|---|---|
| Coding | 3 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 3 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index33
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 72.8% | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | Not measured | 66.3% | Only GPT-5.2-Codex measured |
| LMArena WebDev | 1435 | 1339 | Gemini 3.5 Flash Lite |
| AA Coding Index | 49.3 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LiveCodeBench (Vals AI) | 79.0% | 88.0% | GPT-5.2-Codex |
| SWE-bench Verified (Vals AI) | 75.0% | 72.4% | Gemini 3.5 Flash Lite |
| Vibe Code Bench (Vals AI) | 37.2% | 37.9% | GPT-5.2-Codex |
| Code migration (Vals AI) | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| CyberBench (Vals AI) | 59.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 41.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 37.1% | Only GPT-5.2-Codex measured |
| Terminal-Bench | Not measured | 66.5% | Only GPT-5.2-Codex measured |
| WeirdML | 39.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ALE-Bench | 765.3 | 1299.9 | GPT-5.2-Codex |
| LMArena Text: coding | 1453 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: software and IT | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena WebDev: React | 1408 | 1329 | Gemini 3.5 Flash Lite |
| LMArena WebDev: HTML | Not measured | 1348 | Only GPT-5.2-Codex measured |
| LMArena WebDev: from an image | 1448 | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.2 | 28.5 | GPT-5.2-Codex |
| Epoch Capabilities Index | 144.9 | Not measured | Only Gemini 3.5 Flash Lite measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| AA Agentic Index | 14.3 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Design Arena: agents building web apps | Not measured | 1051 | Only GPT-5.2-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 993 | Only GPT-5.2-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1090 | Only GPT-5.2-Codex measured |
| Design Arena: agents building Android apps | Not measured | 1176 | Only GPT-5.2-Codex measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GPT-5.2-Codex measured |
| Finance Agent (Vals AI) | 47.4% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Tax Agent Bench (Vals AI) | 7.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Legal Research Bench (Vals AI) | 13.9% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Excel Modeling Benchmark (Vals AI) | 43.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| τ²-Bench Telecom | Not measured | 92.1% | Only GPT-5.2-Codex measured |
| APEX-Agents | 29.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| GPQA Diamond | 83.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MMMU Pro (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 83.8% | 89.9% | GPT-5.2-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 18.8% | 35.7% | GPT-5.2-Codex |
| GPQA Diamond (Epoch AI run) | 83.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ARC-AGI | 53.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ARC-AGI-2 | 10.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Chess puzzles | 21.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Mystery game puzzles | 19.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: hard prompts | 1441 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: expert | 1434 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: hard prompts in English | 1440 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: diagrams | 1284 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: homework | 1291 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| FrontierMath, tiers 1 to 3 | 26.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ProofBench | 13.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: math | 1434 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: mathematical work | 1433 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| MMLU Pro | 85.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LegalBench (Vals AI) | 84.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| CorpFin (Vals AI) | 60.7% | Not measured | Only Gemini 3.5 Flash Lite measured |
| TaxEval (Vals AI) | 72.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MortgageTax (Vals AI) | 68.7% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedCode (Vals AI) | 43.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: science | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: medicine and healthcare | 1438 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: legal and government | 1431 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: business and finance | 1423 | Not measured | Only Gemini 3.5 Flash Lite measured |
| FACTS Benchmark Suite | 53.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 7 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-Codex | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 51.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SAGE (Vals AI) | 47.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedScribe (Vals AI) | 70.9% | Not measured | Only Gemini 3.5 Flash Lite measured |
| IFBench | Not measured | 77.6% | Only GPT-5.2-Codex measured |
| Long context reasoning (AA-LCR) | 76.0% | 82.3% | GPT-5.2-Codex |
| DTBench | 83.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMCA | 37.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text | 1435 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: instruction following | 1419 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: creative writing | 1421 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: English | 1438 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: non-English | 1427 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Chinese | 1468 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: German | 1454 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Japanese | 1426 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Korean | 1407 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: French | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Spanish | 1441 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Russian | 1443 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Polish | 1437 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: multi-turn | 1445 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: longer queries | 1435 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: writing and language | 1428 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: entertainment and media | 1414 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: English | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: Chinese | 1311 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: reading text | 1280 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: humor | 1287 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: creative writing | 1260 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GPT-5.2-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 3.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 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 3.5 Flash Lite | OpenAI GPT-5.2-Codex |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | July 21, 2026 | January 14, 2026 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.30 | $1.75 |
| Output $/Mtok | $2.50 | $14.00 |
| Coding index | 49.0 | 45.4 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | $0.41 | $0.43 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash Lite better than GPT-5.2-Codex for coding?
Pick Gemini 3.5 Flash Lite for coding: it scores 49.0 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex. Pick GPT-5.2-Codex for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, Gemini 3.5 Flash Lite or GPT-5.2-Codex?
Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.2-Codex costs $1.75 and $14.00. Per solved SWE-bench Verified task, Gemini 3.5 Flash Lite costs $0.41 and GPT-5.2-Codex $0.43.
Which has the bigger context window, Gemini 3.5 Flash Lite or GPT-5.2-Codex?
Gemini 3.5 Flash Lite, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 3.5 Flash Lite vs GPT-5.2-Codex comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash Lite's coding index rests on 3 independent benchmarks and GPT-5.2-Codex's on 3. Where only one model has a result, the page says so instead of naming a winner.