GPT-5.1-Codex-Max vs o3 Mini
o3 Mini costs 2.3x less per output token than GPT-5.1-Codex-Max ($4.40 vs $10.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-5.1-Codex-Max or o3 Mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Max for a larger context window (400K against 200K tokens).
- Shared results
- 1
- GPT-5.1-Codex-Max only
- 5
- o3 Mini only
- 70
- Like-for-like categories
- 1 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
No call
Only o3 Mini has a AA Intelligence Index result, 12.5.
Directional only
Reasoning
GPQA Diamond
No call
Only o3 Mini has a GPQA Diamond result, 75.5%.
Directional only
Math
AIME
No call
Only o3 Mini has a AIME result, 86.5%.
Directional only
Knowledge
MMLU Pro
No call
Only o3 Mini has a MMLU Pro result, 78.7%.
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
o3 Mini
GPT-5.1-Codex-Max $0.0063, o3 Mini $0.0033 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max not benchmarked, o3 Mini not benchmarked.
- Widest category
- Coding, 12.1 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Vals AI): GPT-5.1-Codex-Max 83.6% against o3 Mini 71.5%, 12.1 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Max $10.00 against o3 Mini $4.40 per million output tokens, 2.3x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K tokens, o3 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 | o3 Mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 60.4% | Only o3 Mini measured |
| SWE-bench Verified | Not measured | 42.4% | Only o3 Mini measured |
| SWE-bench Lite | Not measured | 32.3% | Only o3 Mini measured |
| LiveCodeBench (Vals AI) | 83.6% | 71.5% | 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 | 73.4% | Only o3 Mini measured |
| SciCode | Not measured | 42.8% | Only o3 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 6.8% | Only o3 Mini measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| GSO-Bench | Not measured | 1.3% | Only o3 Mini measured |
| WeirdML | Not measured | 43.7% | Only o3 Mini measured |
| Cybench | Not measured | 22.5% | Only o3 Mini measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max measured |
| LMArena Text: coding | Not measured | 1378 | Only o3 Mini measured |
| LMArena Text: software and IT | Not measured | 1364 | Only o3 Mini measured |
| SciCode | Not measured | 7.7% | Only o3 Mini measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.5 | Only o3 Mini measured |
| Epoch Capabilities Index | Not measured | 140.2 | Only o3 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 31.3% | Only o3 Mini measured |
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 75.5% | Only o3 Mini measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.3% | Only o3 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 12.0% | Only o3 Mini measured |
| GPQA Diamond (Epoch AI run) | Not measured | 77.0% | Only o3 Mini measured |
| ARC-AGI | Not measured | 34.5% | Only o3 Mini measured |
| ARC-AGI-2 | Not measured | 3.0% | Only o3 Mini measured |
| SimpleBench | Not measured | 22.8% | Only o3 Mini measured |
| Chess puzzles | Not measured | 15.0% | Only o3 Mini measured |
| Mystery game puzzles | Not measured | 7.0% | Only o3 Mini measured |
| LMArena Text: hard prompts | Not measured | 1365 | Only o3 Mini measured |
| LMArena Text: expert | Not measured | 1364 | Only o3 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1375 | Only o3 Mini measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 86.5% | Only o3 Mini measured |
| MATH 500 (Vals AI) | Not measured | 91.8% | Only o3 Mini measured |
| MGSM (Vals AI) | Not measured | 91.3% | Only o3 Mini measured |
| OTIS Mock AIME | Not measured | 76.9% | Only o3 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 18.6% | Only o3 Mini measured |
| FrontierMath, tier 4 | Not measured | 0.0% | Only o3 Mini measured |
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max measured |
| MATH level 5 | Not measured | 96.5% | Only o3 Mini measured |
| LMArena Text: math | Not measured | 1396 | Only o3 Mini measured |
| LMArena Text: mathematical work | Not measured | 1399 | Only o3 Mini measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 78.7% | Only o3 Mini measured |
| LegalBench (Vals AI) | Not measured | 71.5% | Only o3 Mini measured |
| CorpFin (Vals AI) | Not measured | 45.3% | Only o3 Mini measured |
| TaxEval (Vals AI) | Not measured | 69.4% | Only o3 Mini measured |
| MedQA (Vals AI) | Not measured | 94.8% | Only o3 Mini measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.2% | Only o3 Mini measured |
| SimpleQA Verified | Not measured | 15.3% | Only o3 Mini measured |
| LMArena Text: science | Not measured | 1339 | Only o3 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1330 | Only o3 Mini measured |
| LMArena Text: legal and government | Not measured | 1328 | Only o3 Mini measured |
| LMArena Text: business and finance | Not measured | 1313 | Only o3 Mini 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 | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 Mini | Leader |
|---|---|---|---|
| IFBench | Not measured | 67.1% | Only o3 Mini measured |
| Long context reasoning (AA-LCR) | Not measured | 43.0% | Only o3 Mini measured |
| DTBench | Not measured | 68.8% | Only o3 Mini measured |
| LMCA | Not measured | 19.0% | Only o3 Mini measured |
| Fiction.LiveBench | Not measured | 50.0% | Only o3 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 61.7% | Only o3 Mini measured |
| LMArena Text | Not measured | 1337 | Only o3 Mini measured |
| LMArena Text: instruction following | Not measured | 1337 | Only o3 Mini measured |
| LMArena Text: creative writing | Not measured | 1286 | Only o3 Mini measured |
| LMArena Text: English | Not measured | 1351 | Only o3 Mini measured |
| LMArena Text: non-English | Not measured | 1319 | Only o3 Mini measured |
| LMArena Text: Chinese | Not measured | 1379 | Only o3 Mini measured |
| LMArena Text: German | Not measured | 1303 | Only o3 Mini measured |
| LMArena Text: Japanese | Not measured | 1286 | Only o3 Mini measured |
| LMArena Text: Korean | Not measured | 1313 | Only o3 Mini measured |
| LMArena Text: French | Not measured | 1334 | Only o3 Mini measured |
| LMArena Text: Spanish | Not measured | 1321 | Only o3 Mini measured |
| LMArena Text: Russian | Not measured | 1304 | Only o3 Mini measured |
| LMArena Text: Polish | Not measured | 1294 | Only o3 Mini measured |
| LMArena Text: multi-turn | Not measured | 1320 | Only o3 Mini measured |
| LMArena Text: longer queries | Not measured | 1343 | Only o3 Mini measured |
| LMArena Text: writing and language | Not measured | 1313 | Only o3 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1283 | Only o3 Mini measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | o3 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
o3 Mini costs less
Repository review
50K input + 3K output tokens
o3 Mini costs less
Agent loop
200K input + 10K output tokens
o3 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 o3 Mini |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 4, 2025 | January 31, 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 o3 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Max for a larger context window (400K against 200K tokens).
Which is cheaper, GPT-5.1-Codex-Max or o3 Mini?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 per million output tokens; o3 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 o3 Mini?
GPT-5.1-Codex-Max, with 400K tokens against 200K.
How many benchmarks is the GPT-5.1-Codex-Max vs o3 Mini comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-5.1-Codex-Max's coding index rests on 1 independent benchmark and o3 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.