Claude Opus 5.5 vs GPT-5.3-Codex
Claude Opus 5.5 leads GPT-5.3-Codex on coding, 88.8 to 60.0 on the Vibe Coding Index, and GPT-5.3-Codex costs 1.4x less per output token ($14.00 vs $20.00 per million). Updated October 22, 2026; 21 benchmarks have a result for both.
vs boards won of 21 shared
Claude Opus 5.5 or GPT-5.3-Codex: which to pick
Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 60.0 for GPT-5.3-Codex.
Pick GPT-5.3-Codex for output tokens 1.4x cheaper ($14.00 vs $20.00 per million).
Model AClaude Opus 5.5Anthropic88.8/1005 independent benchmarksNo cost per solved taskModel BGPT-5.3-CodexOpenAI60.0/1003 independent benchmarks$0.59 per solved task
- Shared results
- 21
- Claude Opus 5.5 only
- 88
- GPT-5.3-Codex only
- 13
- Like-for-like categories
- 6 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
Claude Opus 5.5
Claude Opus 5.5 scores 88.8 against 60.0.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Opus 5.5
Claude Opus 5.5 leads, 57.6 against 32.5.
Same board, both measured
Web design
Design Arena: websites
Claude Opus 5.5
Claude Opus 5.5 leads, 1335 against 1162.
Same board, both measured
General
Vals Index
No call
Only Claude Opus 5.5 has a Vals Index result, 70.2%.
Directional only
Long documents
Listed context window
Claude Opus 5.5
Claude Opus 5.5 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.3-Codex
Claude Opus 5.5 $0.014, 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 5.5 88.8 from 5 benchmarks, GPT-5.3-Codex 60.0 from 3 benchmarks.
- Widest category
- Web design, 33.4 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: 3D: Claude Opus 5.5 1476 against GPT-5.3-Codex 1007, 58.6 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 5.5 $20.00 against GPT-5.3-Codex $14.00 per million output tokens, 1.4x apart.
- Context window
- Claude Opus 5.5 takes 1M 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 5.5 | Bars | GPT-5.3-Codex | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 3 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 7 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 21 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| LiveBench coding | 96.3% | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev | 1807 | 1407 | Claude Opus 5.5 |
| LiveCodeBench (Vals AI) | Not measured | 87.3% | Only GPT-5.3-Codex measured |
| SWE-bench Verified (Vals AI) | Not measured | 78.0% | Only GPT-5.3-Codex measured |
| Terminal-Bench 4 (Vals AI) | 65.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench (Vals AI) | 90.3% | 61.8% | Claude Opus 5.5 |
| Code migration (Vals AI) | 66.7% | Not measured | Only Claude Opus 5.5 measured |
| ProgramBench (Vals AI) | 18.5% | Not measured | Only Claude Opus 5.5 measured |
| IOI (Vals AI) | 95.1% | 53.8% | Claude Opus 5.5 |
| Terminal-Bench 2.1 (Vals AI) | 87.6% | Not measured | Only Claude Opus 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 70.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench 1-100 (Vals AI) | 30.4% | Not measured | Only Claude Opus 5.5 measured |
| CyberBench (Vals AI) | 74.6% | Not measured | Only Claude Opus 5.5 measured |
| SciCode | 66.9% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 53.0% | Only GPT-5.3-Codex measured |
| Terminal-Bench | Not measured | 78.4% | Only GPT-5.3-Codex measured |
| FrontierCode | 54.6% | Not measured | Only Claude Opus 5.5 measured |
| FrontierSWE | 62.3% | Not measured | Only Claude Opus 5.5 measured |
| WeirdML | Not measured | 79.3% | Only GPT-5.3-Codex measured |
| MirrorCode | 77.4% | Not measured | Only Claude Opus 5.5 measured |
| ALE-Bench | 2147.4 | 1655.2 | Claude Opus 5.5 |
| LMArena Text: coding | 1545 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: software and IT | 1538 | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev: React | 1855 | 1395 | Claude Opus 5.5 |
| LMArena WebDev: HTML | 1753 | 1422 | Claude Opus 5.5 |
| LMArena WebDev: from an image | 1753 | 1443 | Claude Opus 5.5 |
| SciCode | 18.5% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 57.6 | 32.5 | Claude Opus 5.5 |
| Epoch Capabilities Index | 168.8 | 157.1 | Claude Opus 5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1316 | 1032 | Claude Opus 5.5 |
| Design Arena: agents building full-stack apps | Not measured | 983 | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | 1308 | 1053 | Claude Opus 5.5 |
| 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 |
| Design Arena: spreadsheets | 1368 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench research | 85.0% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench browser | 80.0% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench long agentic | 85.0% | Not measured | Only Claude Opus 5.5 measured |
| SREBench (Vals AI) | 33.6% | Not measured | Only Claude Opus 5.5 measured |
| Finance Agent (Vals AI) | 58.6% | Not measured | Only Claude Opus 5.5 measured |
| Tax Agent Bench (Vals AI) | 45.6% | Not measured | Only Claude Opus 5.5 measured |
| Legal Research Bench (Vals AI) | 50.5% | Not measured | Only Claude Opus 5.5 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 9.2% | Not measured | Only Claude Opus 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 75.9% | Not measured | Only Claude Opus 5.5 measured |
| BioMysteryBench (Vals AI) | 79.3% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 47.1% | Not measured | Only Claude Opus 5.5 measured |
| Vals Science Index | 58.7% | Not measured | Only Claude Opus 5.5 measured |
| Time Horizon Index (Vals AI) | 91.3% | Not measured | Only Claude Opus 5.5 measured |
| CUA-bench (Vals AI) | 14.0% | Not measured | Only Claude Opus 5.5 measured |
| Robo-bench (Vals AI) | 14.6% | Not measured | Only Claude Opus 5.5 measured |
| τ²-Bench Telecom | Not measured | 86.0% | Only GPT-5.3-Codex measured |
| APEX-Agents | 73.5% | Not measured | Only Claude Opus 5.5 measured |
| METR time horizons | Not measured | 74.5% | Only GPT-5.3-Codex measured |
| Remote Labor Index | 21.3% | Not measured | Only Claude Opus 5.5 measured |
| SpireClimb | 3.3% | Not measured | Only Claude Opus 5.5 measured |
| Vending-Bench 2 | $9,235 | $5,940 | Claude Opus 5.5 |
| LMArena Search | 1213 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.2% | Not measured | Only Claude Opus 5.5 measured |
| MysteryMechanism (Vals AI) | 49.5% | Not measured | Only Claude Opus 5.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 91.5% | Only GPT-5.3-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | 61.4% | 42.5% | Claude Opus 5.5 |
| GPQA Diamond (Epoch AI run) | 90.6% | Not measured | Only Claude Opus 5.5 measured |
| ARC-AGI | 98.5% | Not measured | Only Claude Opus 5.5 measured |
| ARC-AGI-2 | 93.3% | Not measured | Only Claude Opus 5.5 measured |
| Chess puzzles | 67.0% | Not measured | Only Claude Opus 5.5 measured |
| Mystery game puzzles | 71.0% | Not measured | Only Claude Opus 5.5 measured |
| EBR-bench | 71.4% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: hard prompts | 1536 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: expert | 1549 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: hard prompts in English | 1535 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: diagrams | 1345 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: homework | 1362 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only Claude Opus 5.5 measured |
| FrontierMath, tiers 1 to 3 | 91.2% | Not measured | Only Claude Opus 5.5 measured |
| FrontierMath, tier 4 | 95.0% | Not measured | Only Claude Opus 5.5 measured |
| ProofBench | 100.0% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: math | 1518 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: mathematical work | 1516 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 49.8% | Not measured | Only Claude Opus 5.5 measured |
| SimpleQA Verified | 72.2% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: science | 1524 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: medicine and healthcare | 1509 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: legal and government | 1518 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: business and finance | 1494 | Not measured | Only Claude Opus 5.5 measured |
| FACTS Benchmark Suite | 65.3% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | 1335 | 1162 | Claude Opus 5.5 |
| Design Arena: UI components | 1385 | 1134 | Claude Opus 5.5 |
| Design Arena: game dev | 1461 | 1161 | Claude Opus 5.5 |
| Design Arena: data viz | 1397 | 1164 | Claude Opus 5.5 |
| Design Arena: 3D | 1476 | 1007 | Claude Opus 5.5 |
| Design Arena: all code categories | 1390 | 1144 | Claude Opus 5.5 |
| Design Arena: SVG | 1329 | 1129 | Claude Opus 5.5 |
| Design Arena: ASCII art | Not measured | 1152 | Only GPT-5.3-Codex measured |
| LiveBench design | 86.9% | Not measured | Only Claude Opus 5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Opus 5.5 | GPT-5.3-Codex | Leader |
|---|---|---|---|
| Vals Index | 70.2% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench data analysis | 80.3% | Not measured | Only Claude Opus 5.5 measured |
| Public Benefits Bench (Vals AI) | 70.6% | Not measured | Only Claude Opus 5.5 measured |
| SAGE (Vals AI) | 45.8% | Not measured | Only Claude Opus 5.5 measured |
| MedScribe (Vals AI) | 91.4% | Not measured | Only Claude Opus 5.5 measured |
| IFBench | Not measured | 75.4% | Only GPT-5.3-Codex measured |
| Long context reasoning (AA-LCR) | 84.7% | 83.3% | Claude Opus 5.5 |
| DTBench | 98.9% | Not measured | Only Claude Opus 5.5 measured |
| LMCA | 68.2% | Not measured | Only Claude Opus 5.5 measured |
| Furniture assembly | 83.3% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text | 1516 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: instruction following | 1537 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: creative writing | 1535 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision | 1321 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: English | 1519 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: non-English | 1507 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Chinese | 1582 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Japanese | 1534 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: French | 1493 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Spanish | 1508 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Russian | 1517 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: multi-turn | 1501 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: longer queries | 1532 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: writing and language | 1532 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: entertainment and media | 1515 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: English | 1317 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: reading text | 1326 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: creative writing | 1320 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 5.5 | 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
Claude Opus 5.5$0.014Fits in one request
GPT-5.3-Codex$0.0088Fits in one request
GPT-5.3-Codex costs less
Repository review
50K input + 3K output tokens
Claude Opus 5.5$0.260Fits in one request
GPT-5.3-Codex$0.130Fits in one request
GPT-5.3-Codex costs less
Agent loop
200K input + 10K output tokens
Claude Opus 5.5$1.00Fits in one request
GPT-5.3-Codex$0.490Fits in one request
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 5.5 | OpenAI GPT-5.3-Codex |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | February 24, 2026 |
| Context window | 1M | 400K |
| Input $/Mtok | $4.00 | $1.75 |
| Output $/Mtok | $20.00 | $14.00 |
| Coding index | 88.8 | 60.0 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | Not computable | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 5.5 better than GPT-5.3-Codex for coding?
Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 60.0 for GPT-5.3-Codex. Pick GPT-5.3-Codex for output tokens 1.4x cheaper ($14.00 vs $20.00 per million).
Which is cheaper, Claude Opus 5.5 or GPT-5.3-Codex?
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 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 5.5 or GPT-5.3-Codex?
Claude Opus 5.5, with 1M tokens against 400K.
How many benchmarks is the Claude Opus 5.5 vs GPT-5.3-Codex comparison based on?
21 benchmarks have a result for both models as of October 22, 2026. Claude Opus 5.5's coding index rests on 5 independent benchmarks and GPT-5.3-Codex's on 3. Where only one model has a result, the page says so instead of naming a winner.