GPT-4o-mini vs GPT-5.2
GPT-5.2 leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 30.4 to 6.7, and GPT-4o-mini costs 23.3x less per output token ($0.60 vs $14.00 per million). Updated October 21, 2026; 22 benchmarks have a result for both.
GPT-4o-mini or GPT-5.2: which to pick
Only GPT-5.2 has a coding score, 55.9 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding.
Pick GPT-4o-mini for output tokens 23.3x cheaper ($0.60 vs $14.00 per million).
- Shared results
- 22
- GPT-4o-mini only
- 5
- GPT-5.2 only
- 89
- Like-for-like categories
- 6 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
Only GPT-5.2 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.2
GPT-5.2 leads, 30.4 against 6.7.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.2
GPT-5.2 leads, 91.7% against 44.2%.
Same board, both measured
Math
AIME
GPT-5.2
GPT-5.2 leads, 96.9% against 11.5%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.2
GPT-5.2 leads, 86.2% against 62.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.2 has a Design Arena: websites result, 1195.
Directional only
Long documents
Listed context window
GPT-5.2
GPT-5.2 takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini
GPT-4o-mini $0.0004, GPT-5.2 $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2 has the number, $1.91.
Directional only
At a glance
- Coding index
- GPT-4o-mini not benchmarked, GPT-5.2 55.9 from 3 benchmarks.
- Widest category
- Math, 65.5 points apart on average over 4 shared benchmarks.
- Widest single gap
- AIME: GPT-4o-mini 11.5% against GPT-5.2 96.9%, 85.4 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against GPT-5.2 $14.00 per million output tokens, 23.3x apart.
- Context window
- GPT-4o-mini takes 128K tokens, GPT-5.2 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 | GPT-4o-mini | Bars | GPT-5.2 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 4 | ||
| Knowledge | 0 | 6 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 72.8% | Only GPT-5.2 measured |
| SWE-bench Multilingual | Not measured | 66.7% | Only GPT-5.2 measured |
| LMArena WebDev | Not measured | 1417 | Only GPT-5.2 measured |
| AA Coding Index | 11.4 | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Vals AI) | 26.4% | 85.4% | GPT-5.2 |
| SWE-bench Verified (Vals AI) | Not measured | 75.8% | Only GPT-5.2 measured |
| Vibe Code Bench (Vals AI) | Not measured | 53.5% | Only GPT-5.2 measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | 89.4% | GPT-5.2 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 47.0% | Only GPT-5.2 measured |
| Terminal-Bench | Not measured | 64.9% | Only GPT-5.2 measured |
| GSO-Bench | Not measured | 27.5% | Only GPT-5.2 measured |
| WeirdML | Not measured | 72.2% | Only GPT-5.2 measured |
| ALE-Bench | Not measured | 1293.5 | Only GPT-5.2 measured |
| LMArena Text: coding | Not measured | 1442 | Only GPT-5.2 measured |
| LMArena Text: software and IT | Not measured | 1434 | Only GPT-5.2 measured |
| LMArena WebDev: HTML | Not measured | 1427 | Only GPT-5.2 measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 30.4 | GPT-5.2 |
| Epoch Capabilities Index | 126.5 | 153.7 | GPT-5.2 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1086 | Only GPT-5.2 measured |
| Design Arena: agents building full-stack apps | Not measured | 1043 | Only GPT-5.2 measured |
| Design Arena: agents building mobile apps | Not measured | 1093 | Only GPT-5.2 measured |
| Design Arena: agents building Android apps | Not measured | 1058 | Only GPT-5.2 measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GPT-5.2 measured |
| τ²-Bench Telecom | Not measured | 84.8% | Only GPT-5.2 measured |
| METR time horizons | Not measured | 75.3% | Only GPT-5.2 measured |
| Remote Labor Index | Not measured | 2.5% | Only GPT-5.2 measured |
| GDPval | Not measured | 49.7% | Only GPT-5.2 measured |
| DeepResearch Bench | Not measured | 41.1% | Only GPT-5.2 measured |
| Vending-Bench 2 | Not measured | $3,591 | Only GPT-5.2 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | 91.7% | GPT-5.2 |
| MMMU Pro (Vals AI) | 56.6% | 86.7% | GPT-5.2 |
| GPQA Diamond (Artificial Analysis run) | 42.6% | 90.3% | GPT-5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 37.7% | GPT-5.2 |
| GPQA Diamond (Epoch AI run) | Not measured | 91.4% | Only GPT-5.2 measured |
| ARC-AGI | Not measured | 86.2% | Only GPT-5.2 measured |
| ARC-AGI-2 | 0.0% | 52.9% | GPT-5.2 |
| SimpleBench | Not measured | 45.8% | Only GPT-5.2 measured |
| Chess puzzles | Not measured | 48.0% | Only GPT-5.2 measured |
| Mystery game puzzles | Not measured | 23.0% | Only GPT-5.2 measured |
| EBR-bench | Not measured | 23.0% | Only GPT-5.2 measured |
| VPCT | Not measured | 84.0% | Only GPT-5.2 measured |
| LMArena Text: hard prompts | Not measured | 1428 | Only GPT-5.2 measured |
| LMArena Text: expert | Not measured | 1445 | Only GPT-5.2 measured |
| LMArena Text: hard prompts in English | Not measured | 1431 | Only GPT-5.2 measured |
| LMArena Vision: diagrams | Not measured | 1265 | Only GPT-5.2 measured |
| LMArena Vision: homework | Not measured | 1276 | Only GPT-5.2 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| AIME | 11.5% | 96.9% | GPT-5.2 |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | 94.0% | GPT-5.2 |
| AA Math Index | 14.7 | 99.0 | GPT-5.2 |
| AIME 2025 (Artificial Analysis run) | 14.7% | 99.0% | GPT-5.2 |
| OTIS Mock AIME | Not measured | 96.1% | Only GPT-5.2 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 67.4% | Only GPT-5.2 measured |
| FrontierMath, tier 4 | Not measured | 31.7% | Only GPT-5.2 measured |
| ProofBench | Not measured | 15.0% | Only GPT-5.2 measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1440 | Only GPT-5.2 measured |
| LMArena Text: mathematical work | Not measured | 1442 | Only GPT-5.2 measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | 86.2% | GPT-5.2 |
| LegalBench (Vals AI) | Not measured | 82.8% | Only GPT-5.2 measured |
| CaseLaw (Vals AI) | Not measured | 66.0% | Only GPT-5.2 measured |
| CorpFin (Vals AI) | 45.5% | 65.9% | GPT-5.2 |
| TaxEval (Vals AI) | 60.5% | 75.8% | GPT-5.2 |
| MortgageTax (Vals AI) | 54.5% | 67.1% | GPT-5.2 |
| MedQA (Vals AI) | 72.4% | 94.1% | GPT-5.2 |
| MedCode (Vals AI) | Not measured | 49.8% | Only GPT-5.2 measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | 87.4% | GPT-5.2 |
| SimpleQA Verified | Not measured | 37.1% | Only GPT-5.2 measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: science | Not measured | 1425 | Only GPT-5.2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1425 | Only GPT-5.2 measured |
| LMArena Text: legal and government | Not measured | 1427 | Only GPT-5.2 measured |
| LMArena Text: business and finance | Not measured | 1414 | Only GPT-5.2 measured |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1195 | Only GPT-5.2 measured |
| Design Arena: UI components | Not measured | 1190 | Only GPT-5.2 measured |
| Design Arena: game dev | Not measured | 1195 | Only GPT-5.2 measured |
| Design Arena: data viz | Not measured | 1202 | Only GPT-5.2 measured |
| Design Arena: 3D | Not measured | 1079 | Only GPT-5.2 measured |
| Design Arena: all code categories | Not measured | 1170 | Only GPT-5.2 measured |
| Design Arena: SVG | Not measured | 1139 | Only GPT-5.2 measured |
| Design Arena: ASCII art | Not measured | 1152 | Only GPT-5.2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4o-mini | GPT-5.2 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 49.3% | Only GPT-5.2 measured |
| MedScribe (Vals AI) | Not measured | 84.4% | Only GPT-5.2 measured |
| IFBench | 31.0% | 75.4% | GPT-5.2 |
| Long context reasoning (AA-LCR) | Not measured | 82.7% | Only GPT-5.2 measured |
| DTBench | 54.4% | 90.9% | GPT-5.2 |
| LMCA | 10.4% | 43.9% | GPT-5.2 |
| CL-bench | Not measured | 18.2% | Only GPT-5.2 measured |
| Furniture assembly | Not measured | 38.3% | Only GPT-5.2 measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini measured |
| LMArena Text | Not measured | 1416 | Only GPT-5.2 measured |
| LMArena Text: instruction following | Not measured | 1409 | Only GPT-5.2 measured |
| LMArena Text: creative writing | Not measured | 1376 | Only GPT-5.2 measured |
| LMArena Vision | Not measured | 1246 | Only GPT-5.2 measured |
| LMArena Text: English | Not measured | 1422 | Only GPT-5.2 measured |
| LMArena Text: non-English | Not measured | 1405 | Only GPT-5.2 measured |
| LMArena Text: Chinese | Not measured | 1447 | Only GPT-5.2 measured |
| LMArena Text: German | Not measured | 1444 | Only GPT-5.2 measured |
| LMArena Text: Japanese | Not measured | 1420 | Only GPT-5.2 measured |
| LMArena Text: Korean | Not measured | 1374 | Only GPT-5.2 measured |
| LMArena Text: French | Not measured | 1454 | Only GPT-5.2 measured |
| LMArena Text: Spanish | Not measured | 1413 | Only GPT-5.2 measured |
| LMArena Text: Russian | Not measured | 1415 | Only GPT-5.2 measured |
| LMArena Text: Polish | Not measured | 1426 | Only GPT-5.2 measured |
| LMArena Text: multi-turn | Not measured | 1419 | Only GPT-5.2 measured |
| LMArena Text: longer queries | Not measured | 1413 | Only GPT-5.2 measured |
| LMArena Text: writing and language | Not measured | 1392 | Only GPT-5.2 measured |
| LMArena Text: entertainment and media | Not measured | 1378 | Only GPT-5.2 measured |
| LMArena Vision: English | Not measured | 1243 | Only GPT-5.2 measured |
| LMArena Vision: Chinese | Not measured | 1305 | Only GPT-5.2 measured |
| LMArena Vision: reading text | Not measured | 1257 | Only GPT-5.2 measured |
| LMArena Vision: humor | Not measured | 1227 | Only GPT-5.2 measured |
| LMArena Vision: captioning | Not measured | 1267 | Only GPT-5.2 measured |
| LMArena Vision: recognizing things | Not measured | 1232 | Only GPT-5.2 measured |
| LMArena Vision: creative writing | Not measured | 1225 | Only GPT-5.2 measured |
| LMArena Document | Not measured | 1405 | Only GPT-5.2 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | GPT-5.2 | 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
GPT-4o-mini costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini 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 | OpenAI GPT-4o-mini | OpenAI GPT-5.2 |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | July 18, 2024 | December 10, 2025 |
| Context window | 128K | 400K |
| Input $/Mtok | $0.15 | $1.75 |
| Output $/Mtok | $0.60 | $14.00 |
| Coding index | Not benchmarked | 55.9 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $1.91 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini better than GPT-5.2 for coding?
Only GPT-5.2 has a coding score, 55.9 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding. Pick GPT-4o-mini for output tokens 23.3x cheaper ($0.60 vs $14.00 per million).
Which is cheaper, GPT-4o-mini or GPT-5.2?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Cost per solved task is known for GPT-5.2 only.
Which has the bigger context window, GPT-4o-mini or GPT-5.2?
GPT-5.2, with 400K tokens against 128K.
How many benchmarks is the GPT-4o-mini vs GPT-5.2 comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. GPT-4o-mini's coding index rests on 0 independent benchmarks and GPT-5.2's on 3. Where only one model has a result, the page says so instead of naming a winner.