GPT-5.1-Codex vs o4 Mini
Updated October 21, 2026. 18 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick o4 Mini for coding: it scores 68.6 on the Vibe Coding Index against 50.5 for GPT-5.1-Codex.
Pick GPT-5.1-Codex when the context window is larger, 400K against 200K tokens, or when what matters is SWE-bench Verified or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 18
- GPT-5.1-Codex only
- 8
- o4 Mini only
- 76
- Like-for-like categories
- 8 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, four public coding benchmarks
o4 Mini
o4 Mini scores 68.6 against 50.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.1-Codex
GPT-5.1-Codex leads, 23.7 against 16.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only o4 Mini has a GPQA Diamond result, 74.5%.
Directional only
Math
AIME
No call
Only o4 Mini has a AIME result, 83.7%.
Directional only
Knowledge
MMLU Pro
No call
Only o4 Mini has a MMLU Pro result, 80.6%.
Directional only
Web design
Design Arena: websites
GPT-5.1-Codex
GPT-5.1-Codex leads, 1162 against 985.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex
GPT-5.1-Codex takes 400K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
o4 Mini
GPT-5.1-Codex $0.0063, o4 Mini $0.0033 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- GPT-5.1-Codex 50.5 from 2 benchmarks, o4 Mini 68.6 from 2 benchmarks.
- Widest category
- Agentic work, 27.5 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: UI components: GPT-5.1-Codex 1237 against o4 Mini 983, 31.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against o4 Mini $4.40 per million output tokens, 2.3x apart.
- Context window
- GPT-5.1-Codex takes 400K tokens, o4 Mini 200K.
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-5.1-Codex | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 3 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 17 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index31
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 72.0% | Only o4 Mini measured |
| SWE-bench Verified | 66.0% | 64.6% | GPT-5.1-Codex |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| LMArena WebDev | 1337 | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Vals AI) | 85.5% | 82.2% | GPT-5.1-Codex |
| Vibe Code Bench (Vals AI) | 13.1% | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 84.9% | 85.9% | o4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 15.2% | GPT-5.1-Codex |
| Terminal-Bench | 57.8% | Not measured | Only GPT-5.1-Codex measured |
| GSO-Bench | Not measured | 3.6% | Only o4 Mini measured |
| WeirdML | Not measured | 52.6% | Only o4 Mini measured |
| ALE-Bench | 1244.9 | Not measured | Only GPT-5.1-Codex measured |
| LMArena Text: coding | Not measured | 1368 | Only o4 Mini measured |
| LMArena Text: software and IT | Not measured | 1367 | Only o4 Mini measured |
| LMArena WebDev: HTML | 1346 | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 16.7 | GPT-5.1-Codex |
| Epoch Capabilities Index | Not measured | 145.5 | Only o4 Mini measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1018 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | 1086 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | 1191 | Not measured | Only GPT-5.1-Codex measured |
| τ²-Bench Telecom | 83.0% | 55.6% | GPT-5.1-Codex |
| METR time horizons | Not measured | 63.9% | Only o4 Mini measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 74.5% | Only o4 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 79.7% | Only o4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 86.0% | 78.4% | GPT-5.1-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 16.5% | GPT-5.1-Codex |
| GPQA Diamond (Epoch AI run) | Not measured | 79.6% | Only o4 Mini measured |
| ARC-AGI | Not measured | 58.7% | Only o4 Mini measured |
| ARC-AGI-2 | Not measured | 6.1% | Only o4 Mini measured |
| SimpleBench | Not measured | 38.7% | Only o4 Mini measured |
| Chess puzzles | Not measured | 22.0% | Only o4 Mini measured |
| Mystery game puzzles | Not measured | 5.0% | Only o4 Mini measured |
| VPCT | Not measured | 57.5% | Only o4 Mini measured |
| LMArena Text: hard prompts | Not measured | 1351 | Only o4 Mini measured |
| LMArena Text: expert | Not measured | 1343 | Only o4 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1366 | Only o4 Mini measured |
| LMArena Vision: diagrams | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: homework | Not measured | 1234 | Only o4 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 83.7% | Only o4 Mini measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only o4 Mini measured |
| MGSM (Vals AI) | Not measured | 93.4% | Only o4 Mini measured |
| AA Math Index | 95.7 | 90.7 | GPT-5.1-Codex |
| AIME 2025 (Artificial Analysis run) | 95.7% | 90.7% | GPT-5.1-Codex |
| OTIS Mock AIME | Not measured | 81.7% | Only o4 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 36.1% | Only o4 Mini measured |
| FrontierMath, tier 4 | Not measured | 4.9% | Only o4 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only o4 Mini measured |
| LMArena Text: math | Not measured | 1389 | Only o4 Mini measured |
| LMArena Text: mathematical work | Not measured | 1379 | Only o4 Mini measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 80.6% | Only o4 Mini measured |
| LegalBench (Vals AI) | Not measured | 79.2% | Only o4 Mini measured |
| CorpFin (Vals AI) | Not measured | 59.0% | Only o4 Mini measured |
| TaxEval (Vals AI) | Not measured | 74.8% | Only o4 Mini measured |
| MortgageTax (Vals AI) | Not measured | 64.8% | Only o4 Mini measured |
| MedQA (Vals AI) | Not measured | 96.0% | Only o4 Mini measured |
| MedCode (Vals AI) | Not measured | 33.8% | Only o4 Mini measured |
| MMLU Pro (Artificial Analysis run) | 86.0% | 83.2% | GPT-5.1-Codex |
| SimpleQA Verified | Not measured | 19.6% | Only o4 Mini measured |
| GeoBench | Not measured | 64.0% | Only o4 Mini measured |
| LMArena Text: science | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1361 | Only o4 Mini measured |
| LMArena Text: legal and government | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: business and finance | Not measured | 1325 | Only o4 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 985 | GPT-5.1-Codex |
| Design Arena: UI components | 1237 | 983 | GPT-5.1-Codex |
| Design Arena: game dev | 1138 | 1004 | GPT-5.1-Codex |
| Design Arena: data viz | 1213 | 990 | GPT-5.1-Codex |
| Design Arena: 3D | Not measured | 854 | Only o4 Mini measured |
| Design Arena: all code categories | 1153 | 977 | GPT-5.1-Codex |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | o4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.1% | Only o4 Mini measured |
| MedScribe (Vals AI) | Not measured | 69.1% | Only o4 Mini measured |
| IFBench | 70.0% | 68.7% | GPT-5.1-Codex |
| Long context reasoning (AA-LCR) | 69.3% | 61.0% | GPT-5.1-Codex |
| DTBench | Not measured | 77.6% | Only o4 Mini measured |
| LMCA | Not measured | 26.5% | Only o4 Mini measured |
| Fiction.LiveBench | Not measured | 77.8% | Only o4 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 75.0% | Only o4 Mini measured |
| LMArena Text | Not measured | 1353 | Only o4 Mini measured |
| LMArena Text: instruction following | Not measured | 1320 | Only o4 Mini measured |
| LMArena Text: creative writing | Not measured | 1294 | Only o4 Mini measured |
| LMArena Vision | Not measured | 1194 | Only o4 Mini measured |
| LMArena Text: English | Not measured | 1367 | Only o4 Mini measured |
| LMArena Text: non-English | Not measured | 1337 | Only o4 Mini measured |
| LMArena Text: Chinese | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: German | Not measured | 1336 | Only o4 Mini measured |
| LMArena Text: Japanese | Not measured | 1308 | Only o4 Mini measured |
| LMArena Text: Korean | Not measured | 1312 | Only o4 Mini measured |
| LMArena Text: French | Not measured | 1364 | Only o4 Mini measured |
| LMArena Text: Spanish | Not measured | 1346 | Only o4 Mini measured |
| LMArena Text: Russian | Not measured | 1334 | Only o4 Mini measured |
| LMArena Text: Polish | Not measured | 1358 | Only o4 Mini measured |
| LMArena Text: multi-turn | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: longer queries | Not measured | 1315 | Only o4 Mini measured |
| LMArena Text: writing and language | Not measured | 1316 | Only o4 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1308 | Only o4 Mini measured |
| LMArena Vision: English | Not measured | 1200 | Only o4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: reading text | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: humor | Not measured | 1199 | Only o4 Mini measured |
| LMArena Vision: captioning | Not measured | 1204 | Only o4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1166 | Only o4 Mini measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex | o4 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
o4 Mini costs less
Repository review
50K input + 3K output tokens
o4 Mini costs less
Agent loop
200K input + 10K output tokens
o4 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-5.1-Codex | OpenAI o4 Mini |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | November 13, 2025 | April 16, 2025 |
| Context window | 400K | 200K |
| Input $/Mtok | $1.25 | $1.10 |
| Output $/Mtok | $10.00 | $4.40 |
| Coding index | 50.5 | 68.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.892 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than o4 Mini for coding?
Pick o4 Mini for coding: it scores 68.6 on the Vibe Coding Index against 50.5 for GPT-5.1-Codex. Pick GPT-5.1-Codex when the context window is larger, 400K against 200K tokens, or when what matters is SWE-bench Verified or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, GPT-5.1-Codex or o4 Mini?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, GPT-5.1-Codex or o4 Mini?
GPT-5.1-Codex, with 400K tokens against 200K.
How many benchmarks is the GPT-5.1-Codex vs o4 Mini comparison based on?
18 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex's coding index rests on 2 independent benchmarks and o4 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.