GPT-4o (2024-11-20) vs GPT-5.1-Codex-Max
GPT-4o (2024-11-20) and GPT-5.1-Codex-Max cost about the same per output token ($10.00 vs $10.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-4o (2024-11-20) or GPT-5.1-Codex-Max: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o (2024-11-20) for work measured by LiveCodeBench (Vals AI), where it leads.
- Shared results
- 1
- GPT-4o (2024-11-20) only
- 23
- GPT-5.1-Codex-Max only
- 5
- 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 GPT-4o (2024-11-20) has a AA Intelligence Index result, 8.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-11-20) has a GPQA Diamond result, 53.8%.
Directional only
Math
AIME
No call
Only GPT-4o (2024-11-20) has a AIME result, 11.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-11-20) has a MMLU Pro result, 72.6%.
Directional only
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.1-Codex-Max
GPT-4o (2024-11-20) $0.0075, GPT-5.1-Codex-Max $0.0063 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-11-20) not benchmarked, GPT-5.1-Codex-Max not benchmarked.
- Widest category
- Coding, 40.1 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Vals AI): GPT-4o (2024-11-20) 43.4% against GPT-5.1-Codex-Max 83.6%, 40.1 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- Context window
- GPT-4o (2024-11-20) takes 128K tokens, GPT-5.1-Codex-Max 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 (2024-11-20) | Bars | GPT-5.1-Codex-Max | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Aider polyglot | 18.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| LiveCodeBench (Vals AI) | 43.4% | 83.6% | GPT-5.1-Codex-Max |
| Vibe Code Bench (Vals AI) | Not measured | 22.2% | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench | Not measured | 60.4% | Only GPT-5.1-Codex-Max measured |
| GSO-Bench | 0.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| WeirdML | 25.1% | Not measured | Only GPT-4o (2024-11-20) measured |
| Cybench | 12.5% | Not measured | Only GPT-4o (2024-11-20) measured |
| ALE-Bench | Not measured | 1228.3 | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.4 | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| METR time horizons | Not measured | 70.8% | Only GPT-5.1-Codex-Max measured |
| TheAgentCompany | 8.6% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| GPQA Diamond | 53.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| MMMU Pro (Vals AI) | 62.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| GPQA Diamond (Epoch AI run) | 47.9% | Not measured | Only GPT-4o (2024-11-20) measured |
| VPCT | 40.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AIME | 11.9% | Not measured | Only GPT-4o (2024-11-20) measured |
| MATH 500 (Vals AI) | 74.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| MGSM (Vals AI) | 90.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| OTIS Mock AIME | 6.3% | Not measured | Only GPT-4o (2024-11-20) measured |
| ProofBench | Not measured | 9.0% | Only GPT-5.1-Codex-Max measured |
| MATH level 5 | 49.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| MMLU Pro | 72.6% | Not measured | Only GPT-4o (2024-11-20) measured |
| LegalBench (Vals AI) | 82.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| CaseLaw (Vals AI) | 59.7% | Not measured | Only GPT-4o (2024-11-20) measured |
| CorpFin (Vals AI) | 45.9% | Not measured | Only GPT-4o (2024-11-20) measured |
| TaxEval (Vals AI) | 74.5% | Not measured | Only GPT-4o (2024-11-20) measured |
| MortgageTax (Vals AI) | 57.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| GeoBench | 71.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Creative writing (Lech Mazur) | 81.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 47 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | GPT-5.1-Codex-Max | 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-5.1-Codex-Max costs less
Repository review
50K input + 3K output tokens
GPT-5.1-Codex-Max costs less
Agent loop
200K input + 10K output tokens
GPT-5.1-Codex-Max 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 (2024-11-20) | OpenAI GPT-5.1-Codex-Max |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | November 20, 2024 | December 4, 2025 |
| Context window | 128K | 400K |
| Input $/Mtok | $2.50 | $1.25 |
| Output $/Mtok | $10.00 | $10.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o (2024-11-20) better than GPT-5.1-Codex-Max for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-11-20) for work measured by LiveCodeBench (Vals AI), where it leads.
Which is cheaper, GPT-4o (2024-11-20) or GPT-5.1-Codex-Max?
GPT-4o (2024-11-20) costs $2.50 per million input tokens and $10.00 per million output tokens; GPT-5.1-Codex-Max costs $1.25 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-11-20) or GPT-5.1-Codex-Max?
GPT-5.1-Codex-Max, with 400K tokens against 128K.
How many benchmarks is the GPT-4o (2024-11-20) vs GPT-5.1-Codex-Max comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-11-20)'s coding index rests on 0 independent benchmarks and GPT-5.1-Codex-Max's on 1. Where only one model has a result, the page says so instead of naming a winner.