Claude Opus 4.1 vs GPT-5.3-Codex
Updated October 21, 2026. 16 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-5.3-Codex for coding: it scores 29.5 on the Vibe Coding Index against 27.2 for Claude Opus 4.1.
Pick Claude Opus 4.1 when what matters is Design Arena: websites or Design Arena: UI components, where it leads.
- Shared results
- 16
- Claude Opus 4.1 only
- 55
- GPT-5.3-Codex only
- 18
- Like-for-like categories
- 4 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-5.3-Codex
GPT-5.3-Codex scores 29.5 against 27.2.
One benchmark behind each score
Intelligence
AA Intelligence Index
GPT-5.3-Codex
GPT-5.3-Codex leads, 32.5 against 22.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Claude Opus 4.1 has a GPQA Diamond result, 76.3%.
Directional only
Math
AIME
No call
Only Claude Opus 4.1 has a AIME result, 78.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Opus 4.1 has a MMLU Pro result, 87.9%.
Directional only
Web design
Design Arena: websites
Claude Opus 4.1
Claude Opus 4.1 leads, 1177 against 1163.
Same board, both measured
Long documents
Listed context window
GPT-5.3-Codex
GPT-5.3-Codex takes 400K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.3-Codex
Claude Opus 4.1 $0.052, GPT-5.3-Codex $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.3-Codex has the number, $0.59.
Directional only
At a glance
- Coding index
- Claude Opus 4.1 27.2 from 1 benchmark, GPT-5.3-Codex 29.5 from 1 benchmark.
- Widest category
- Coding, 20.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- Terminal-Bench: Claude Opus 4.1 38.0% against GPT-5.3-Codex 78.4%, 40.4 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 4.1 $75.00 against GPT-5.3-Codex $14.00 per million output tokens, 5.4x apart.
- Context window
- Claude Opus 4.1 takes 200K tokens, GPT-5.3-Codex 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 | Claude Opus 4.1 | Bars | GPT-5.3-Codex | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Web design | 8 | 0 | ||
| All shared boards | 8 | 8 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| LMArena WebDev | 1390 | 1407 | GPT-5.3-Codex |
| LiveCodeBench (Vals AI) | 66.5% | 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) | Not measured | 61.8% | Only GPT-5.3-Codex measured |
| IOI (Vals AI) | Not measured | 53.8% | Only GPT-5.3-Codex measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 53.0% | Only GPT-5.3-Codex measured |
| Terminal-Bench | 38.0% | 78.4% | GPT-5.3-Codex |
| WeirdML | 45.9% | 79.3% | GPT-5.3-Codex |
| Cybench | 42.0% | Not measured | Only Claude Opus 4.1 measured |
| ALE-Bench | Not measured | 1655.2 | Only GPT-5.3-Codex measured |
| LMArena Text: coding | 1479 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: software and IT | 1456 | Not measured | Only Claude Opus 4.1 measured |
| LMArena WebDev: React | Not measured | 1395 | Only GPT-5.3-Codex measured |
| LMArena WebDev: HTML | 1399 | 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 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | 32.5 | GPT-5.3-Codex |
| Epoch Capabilities Index | 144.1 | 157.1 | GPT-5.3-Codex |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1033 | Only GPT-5.3-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 983 | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1054 | Only GPT-5.3-Codex measured |
| 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 | Not measured | 86.0% | Only GPT-5.3-Codex measured |
| METR time horizons | 66.8% | 74.5% | GPT-5.3-Codex |
| GDPval | 43.6% | Not measured | Only Claude Opus 4.1 measured |
| DeepResearch Bench | 48.3% | Not measured | Only Claude Opus 4.1 measured |
| Vending-Bench 2 | Not measured | $5,940 | Only GPT-5.3-Codex measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| GPQA Diamond | 76.3% | Not measured | Only Claude Opus 4.1 measured |
| MMMU Pro (Vals AI) | 77.5% | Not measured | Only Claude Opus 4.1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 91.5% | Only GPT-5.3-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 42.5% | Only GPT-5.3-Codex measured |
| GPQA Diamond (Epoch AI run) | 77.3% | Not measured | Only Claude Opus 4.1 measured |
| SimpleBench | 60.0% | Not measured | Only Claude Opus 4.1 measured |
| Mystery game puzzles | 21.0% | Not measured | Only Claude Opus 4.1 measured |
| EBR-bench | 7.9% | Not measured | Only Claude Opus 4.1 measured |
| VPCT | 35.0% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: hard prompts | 1442 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: expert | 1438 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: hard prompts in English | 1451 | Not measured | Only Claude Opus 4.1 measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AIME | 78.2% | Not measured | Only Claude Opus 4.1 measured |
| MATH 500 (Vals AI) | 95.4% | Not measured | Only Claude Opus 4.1 measured |
| MGSM (Vals AI) | 94.4% | Not measured | Only Claude Opus 4.1 measured |
| OTIS Mock AIME | 68.9% | Not measured | Only Claude Opus 4.1 measured |
| FrontierMath, tiers 1 to 3 | 12.6% | Not measured | Only Claude Opus 4.1 measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: math | 1431 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: mathematical work | 1434 | Not measured | Only Claude Opus 4.1 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| MMLU Pro | 87.9% | Not measured | Only Claude Opus 4.1 measured |
| LegalBench (Vals AI) | 83.5% | Not measured | Only Claude Opus 4.1 measured |
| TaxEval (Vals AI) | 73.7% | Not measured | Only Claude Opus 4.1 measured |
| MortgageTax (Vals AI) | 61.1% | Not measured | Only Claude Opus 4.1 measured |
| MedQA (Vals AI) | 93.6% | Not measured | Only Claude Opus 4.1 measured |
| MedCode (Vals AI) | 47.2% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: science | 1422 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: medicine and healthcare | 1416 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: legal and government | 1421 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: business and finance | 1406 | Not measured | Only Claude Opus 4.1 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | 1177 | 1163 | Claude Opus 4.1 |
| Design Arena: UI components | 1164 | 1137 | Claude Opus 4.1 |
| Design Arena: game dev | 1172 | 1162 | Claude Opus 4.1 |
| Design Arena: data viz | 1166 | 1164 | Claude Opus 4.1 |
| Design Arena: 3D | 1153 | 1008 | Claude Opus 4.1 |
| Design Arena: all code categories | 1171 | 1145 | Claude Opus 4.1 |
| Design Arena: SVG | 1152 | 1129 | Claude Opus 4.1 |
| Design Arena: ASCII art | 1167 | 1151 | Claude Opus 4.1 |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
| Benchmark | Claude Opus 4.1 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 31.4% | Not measured | Only Claude Opus 4.1 measured |
| MedScribe (Vals AI) | 73.9% | Not measured | Only Claude Opus 4.1 measured |
| IFBench | Not measured | 75.4% | Only GPT-5.3-Codex measured |
| Long context reasoning (AA-LCR) | Not measured | 83.3% | Only GPT-5.3-Codex measured |
| DTBench | 80.0% | Not measured | Only Claude Opus 4.1 measured |
| LMCA | 37.1% | Not measured | Only Claude Opus 4.1 measured |
| Creative writing (Lech Mazur) | 84.7% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text | 1419 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: instruction following | 1435 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: creative writing | 1412 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: English | 1433 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: non-English | 1405 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Chinese | 1427 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: German | 1413 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Japanese | 1377 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Korean | 1381 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: French | 1433 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Spanish | 1448 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Russian | 1422 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: Polish | 1413 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: multi-turn | 1444 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: longer queries | 1455 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: writing and language | 1418 | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: entertainment and media | 1398 | Not measured | Only Claude Opus 4.1 measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.1 | 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-5.3-Codex costs less
Repository review
50K input + 3K output tokens
GPT-5.3-Codex costs less
Agent loop
200K input + 10K output tokens
GPT-5.3-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 | Anthropic Claude Opus 4.1 | OpenAI GPT-5.3-Codex |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 5, 2025 | February 24, 2026 |
| Context window | 200K | 400K |
| Input $/Mtok | $15.00 | $1.75 |
| Output $/Mtok | $75.00 | $14.00 |
| Coding index | 27.2 | 29.5 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 4.1 better than GPT-5.3-Codex for coding?
Pick GPT-5.3-Codex for coding: it scores 29.5 on the Vibe Coding Index against 27.2 for Claude Opus 4.1. Pick Claude Opus 4.1 when what matters is Design Arena: websites or Design Arena: UI components, where it leads.
Which is cheaper, Claude Opus 4.1 or GPT-5.3-Codex?
Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 per million output tokens; GPT-5.3-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.3-Codex only.
Which has the bigger context window, Claude Opus 4.1 or GPT-5.3-Codex?
GPT-5.3-Codex, with 400K tokens against 200K.
How many benchmarks is the Claude Opus 4.1 vs GPT-5.3-Codex comparison based on?
16 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.1's coding index rests on 1 independent benchmark and GPT-5.3-Codex's on 1. Where only one model has a result, the page says so instead of naming a winner.