GPT-5.1-Codex vs GPT-5.3-Codex
Updated October 21, 2026. 21 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 29.5 for GPT-5.3-Codex.
Pick GPT-5.3-Codex when a solved task costs $0.59 against $0.892, or when what matters is LMArena WebDev or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 21
- GPT-5.1-Codex only
- 5
- GPT-5.3-Codex only
- 13
- Like-for-like categories
- 6 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
GPT-5.1-Codex
GPT-5.1-Codex scores 50.5 against 29.5.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.3-Codex
GPT-5.3-Codex leads, 32.5 against 23.7.
Same board, both measured
Web design
Design Arena: websites
GPT-5.3-Codex
GPT-5.3-Codex leads, 1163 against 1162.
Same board, both measured
Long documents
Listed context window
No call
Both take 400K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.1-Codex
GPT-5.1-Codex $0.0063, GPT-5.3-Codex $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.3-Codex
GPT-5.1-Codex $0.892, GPT-5.3-Codex $0.59.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.1-Codex 50.5 from 2 benchmarks, GPT-5.3-Codex 29.5 from 1 benchmark.
- Widest category
- Coding, 17.9 points apart on average over 7 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.1-Codex 13.1% against GPT-5.3-Codex 61.8%, 48.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against GPT-5.3-Codex $14.00 per million output tokens, 1.4x apart.
- Context window
- Both take 400K tokens.
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 | GPT-5.3-Codex | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 0 | 2 | ||
| Web design | 3 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 5 | 16 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena WebDev | 1337 | 1407 | GPT-5.3-Codex |
| LiveCodeBench (Vals AI) | 85.5% | 87.3% | GPT-5.3-Codex |
| SWE-bench Verified (Vals AI) | Not measured | 78.0% | Only GPT-5.3-Codex measured |
| Vibe Code Bench (Vals AI) | 13.1% | 61.8% | GPT-5.3-Codex |
| IOI (Vals AI) | Not measured | 53.8% | Only GPT-5.3-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 84.9% | Not measured | Only GPT-5.1-Codex measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 53.0% | GPT-5.3-Codex |
| Terminal-Bench | 57.8% | 78.4% | GPT-5.3-Codex |
| WeirdML | Not measured | 79.3% | Only GPT-5.3-Codex measured |
| ALE-Bench | 1244.9 | 1655.2 | GPT-5.3-Codex |
| LMArena WebDev: React | Not measured | 1395 | Only GPT-5.3-Codex measured |
| LMArena WebDev: HTML | 1346 | 1422 | GPT-5.3-Codex |
| LMArena WebDev: from an image | Not measured | 1443 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 32.5 | GPT-5.3-Codex |
| Epoch Capabilities Index | Not measured | 157.1 | Only GPT-5.3-Codex measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1018 | 1033 | GPT-5.3-Codex |
| Design Arena: agents building full-stack apps | 1086 | 983 | GPT-5.1-Codex |
| Design Arena: agents building mobile apps | 1191 | 1054 | GPT-5.1-Codex |
| Design Arena: agents building Android apps | Not measured | 1084 | Only GPT-5.3-Codex measured |
| Design Arena: agents building Godot games | Not measured | 1124 | Only GPT-5.3-Codex measured |
| τ²-Bench Telecom | 83.0% | 86.0% | GPT-5.3-Codex |
| METR time horizons | Not measured | 74.5% | Only GPT-5.3-Codex measured |
| Vending-Bench 2 | Not measured | $5,940 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.0% | 91.5% | GPT-5.3-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 42.5% | GPT-5.3-Codex |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AA Math Index | 95.7 | Not measured | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | 95.7% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 86.0% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 16 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1163 | GPT-5.3-Codex |
| Design Arena: UI components | 1237 | 1137 | GPT-5.1-Codex |
| Design Arena: game dev | 1138 | 1162 | GPT-5.3-Codex |
| Design Arena: data viz | 1213 | 1164 | GPT-5.1-Codex |
| Design Arena: 3D | Not measured | 1008 | Only GPT-5.3-Codex measured |
| Design Arena: all code categories | 1153 | 1145 | GPT-5.1-Codex |
| Design Arena: SVG | Not measured | 1129 | Only GPT-5.3-Codex measured |
| Design Arena: ASCII art | Not measured | 1151 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | Leader |
|---|---|---|---|
| IFBench | 70.0% | 75.4% | GPT-5.3-Codex |
| Long context reasoning (AA-LCR) | 69.3% | 83.3% | GPT-5.3-Codex |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex | GPT-5.3-Codex | 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 costs less
Repository review
50K input + 3K output tokens
GPT-5.1-Codex costs less
Agent loop
200K input + 10K output tokens
GPT-5.1-Codex 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 GPT-5.3-Codex |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | November 13, 2025 | February 24, 2026 |
| Context window | 400K | 400K |
| Input $/Mtok | $1.25 | $1.75 |
| Output $/Mtok | $10.00 | $14.00 |
| Coding index | 50.5 | 29.5 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.892 | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than GPT-5.3-Codex for coding?
Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 29.5 for GPT-5.3-Codex. Pick GPT-5.3-Codex when a solved task costs $0.59 against $0.892, or when what matters is LMArena WebDev or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, GPT-5.1-Codex or GPT-5.3-Codex?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-5.3-Codex costs $1.75 and $14.00. Per solved SWE-bench Verified task, GPT-5.1-Codex costs $0.892 and GPT-5.3-Codex $0.59.
Which has the bigger context window, GPT-5.1-Codex or GPT-5.3-Codex?
Neither: both take 400K tokens.
How many benchmarks is the GPT-5.1-Codex vs GPT-5.3-Codex comparison based on?
21 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 GPT-5.3-Codex's on 1. Where only one model has a result, the page says so instead of naming a winner.