GPT-5.1-Codex-Max vs o4 Mini
Updated October 21, 2026. 2 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GPT-5.1-Codex-Max has the edge where the context window is larger, 400K against 200K tokens.
- Shared results
- 2
- GPT-5.1-Codex-Max only
- 4
- o4 Mini only
- 92
- Like-for-like categories
- 2 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only o4 Mini has a AA Intelligence Index result, 16.7.
Directional only
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
No call
Only o4 Mini has a Design Arena: websites result, 985.
Directional only
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
o4 Mini
GPT-5.1-Codex-Max $0.0063, o4 Mini $0.0033 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max not benchmarked, o4 Mini not benchmarked.
- Widest category
- Agentic work, 6.9 points apart on average over 1 shared benchmark.
- Widest single gap
- METR time horizons: GPT-5.1-Codex-Max 70.8% against o4 Mini 63.9%, 6.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Max $10.00 against o4 Mini $4.40 per million output tokens, 2.3x apart.
- Context window
- GPT-5.1-Codex-Max 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-Max | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.1-Codex-Max | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 72.0% | Only o4 Mini measured |
| SWE-bench Verified | Not measured | 64.6% | Only o4 Mini measured |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| LiveCodeBench (Vals AI) | 83.6% | 82.2% | GPT-5.1-Codex-Max |
| Vibe Code Bench (Vals AI) | 22.2% | Not measured | Only GPT-5.1-Codex-Max measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 85.9% | Only o4 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only o4 Mini measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| GSO-Bench | Not measured | 3.6% | Only o4 Mini measured |
| WeirdML | Not measured | 52.6% | Only o4 Mini measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max measured |
| LMArena Text: coding | Not measured | 1368 | Only o4 Mini measured |
| LMArena Text: software and IT | Not measured | 1367 | Only o4 Mini measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 16.7 | Only o4 Mini measured |
| 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-Max | o4 Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 55.6% | Only o4 Mini measured |
| METR time horizons | 70.8% | 63.9% | GPT-5.1-Codex-Max |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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) | Not measured | 78.4% | Only o4 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 16.5% | Only o4 Mini measured |
| 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 | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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 | Not measured | 90.7 | Only o4 Mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 90.7% | Only o4 Mini measured |
| 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 |
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max 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 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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) | Not measured | 83.2% | Only o4 Mini measured |
| 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 designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 985 | Only o4 Mini measured |
| Design Arena: UI components | Not measured | 983 | Only o4 Mini measured |
| Design Arena: game dev | Not measured | 1003 | Only o4 Mini measured |
| Design Arena: data viz | Not measured | 990 | Only o4 Mini measured |
| Design Arena: 3D | Not measured | 854 | Only o4 Mini measured |
| Design Arena: all code categories | Not measured | 976 | Only o4 Mini measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index33 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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 | Not measured | 68.7% | Only o4 Mini measured |
| Long context reasoning (AA-LCR) | Not measured | 61.0% | Only o4 Mini measured |
| 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-Max | 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-Max | OpenAI o4 Mini |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 4, 2025 | April 16, 2025 |
| Context window | 400K | 200K |
| Input $/Mtok | $1.25 | $1.10 |
| Output $/Mtok | $10.00 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than o4 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-5.1-Codex-Max has the edge where the context window is larger, 400K against 200K tokens.
Which is cheaper, GPT-5.1-Codex-Max or o4 Mini?
GPT-5.1-Codex-Max 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 neither of them.
Which has the bigger context window, GPT-5.1-Codex-Max or o4 Mini?
GPT-5.1-Codex-Max, with 400K tokens against 200K.
How many benchmarks is the GPT-5.1-Codex-Max vs o4 Mini comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Max's coding index rests on 1 independent benchmark and o4 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.