Claude Opus 5.5 vs GPT-5.1-Codex-Max
GPT-5.1-Codex-Max costs 2.0x less per output token than Claude Opus 5.5 ($10.00 vs $20.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
vs boards won of 3 shared
Claude Opus 5.5 or GPT-5.1-Codex-Max: which to pick
Only Claude Opus 5.5 has a coding score, 88.8 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Max for output tokens 2.0x cheaper ($10.00 vs $20.00 per million).
Model AClaude Opus 5.5Anthropic88.8/1005 independent benchmarksNo cost per solved taskModel BGPT-5.1-Codex-MaxOpenAINot benchmarked1 independent benchmarkNo cost per solved task
- Shared results
- 3
- Claude Opus 5.5 only
- 104
- GPT-5.1-Codex-Max only
- 3
- Like-for-like categories
- 2 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
Only Claude Opus 5.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Claude Opus 5.5 has a AA Intelligence Index result, 57.6.
Directional only
Web design
Design Arena: websites
No call
Only Claude Opus 5.5 has a Design Arena: websites result, 1336.
Directional only
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-5.1-Codex-Max
Claude Opus 5.5 $0.014, GPT-5.1-Codex-Max $0.0063 per turn.
List prices
At a glance
- Coding index
- Claude Opus 5.5 88.8 from 5 benchmarks, GPT-5.1-Codex-Max not benchmarked.
- Widest category
- Math, 91.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: Claude Opus 5.5 100.0% against GPT-5.1-Codex-Max 9.0%, 91.0 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 5.5 $20.00 against GPT-5.1-Codex-Max $10.00 per million output tokens, 2.0x apart.
- Context window
- Claude Opus 5.5 takes 1M 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 | Claude Opus 5.5 | Bars | GPT-5.1-Codex-Max | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Math | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| LiveBench coding | 96.3% | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev | 1807 | Not measured | Only Claude Opus 5.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 83.6% | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench 4 (Vals AI) | 65.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench (Vals AI) | 90.3% | 22.2% | 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% | Not measured | Only Claude Opus 5.5 measured |
| 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 | Not measured | 60.4% | Only GPT-5.1-Codex-Max measured |
| FrontierCode | 54.6% | Not measured | Only Claude Opus 5.5 measured |
| FrontierSWE | 62.3% | Not measured | Only Claude Opus 5.5 measured |
| MirrorCode | 77.4% | Not measured | Only Claude Opus 5.5 measured |
| ALE-Bench | 2147.4 | 1228.3 | 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 | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev: HTML | 1753 | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev: from an image | 1753 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 57.6 | Not measured | Only Claude Opus 5.5 measured |
| Epoch Capabilities Index | 168.8 | Not measured | Only Claude Opus 5.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1317 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: agents building mobile apps | 1310 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: spreadsheets | 1352 | 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 |
| APEX-Agents | 73.5% | Not measured | Only Claude Opus 5.5 measured |
| METR time horizons | Not measured | 70.8% | Only GPT-5.1-Codex-Max 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 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Search | 1213 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 15 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | 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 |
| Humanity's Last Exam (Artificial Analysis run) | 61.4% | Not measured | Only Claude Opus 5.5 measured |
| 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 | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | 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% | 9.0% | Claude Opus 5.5 |
| 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 index6 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | 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 |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1336 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: UI components | 1392 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: game dev | 1458 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: data viz | 1397 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: 3D | 1477 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: all code categories | 1390 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: SVG | 1333 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench design | 86.9% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index27 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-5.1-Codex-Max | 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 |
| Long context reasoning (AA-LCR) | 84.7% | Not measured | Only Claude Opus 5.5 measured |
| 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 5.5 | 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
Claude Opus 5.5$0.014Fits in one request
GPT-5.1-Codex-Max$0.0063Fits in one request
GPT-5.1-Codex-Max costs less
Repository review
50K input + 3K output tokens
Claude Opus 5.5$0.260Fits in one request
GPT-5.1-Codex-Max$0.092Fits in one request
GPT-5.1-Codex-Max costs less
Agent loop
200K input + 10K output tokens
Claude Opus 5.5$1.00Fits in one request
GPT-5.1-Codex-Max$0.350Fits in one request
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 | Anthropic Claude Opus 5.5 | OpenAI GPT-5.1-Codex-Max |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | December 4, 2025 |
| Context window | 1M | 400K |
| Input $/Mtok | $4.00 | $1.25 |
| Output $/Mtok | $20.00 | $10.00 |
| Coding index | 88.8 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 5.5 better than GPT-5.1-Codex-Max for coding?
Only Claude Opus 5.5 has a coding score, 88.8 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Max for output tokens 2.0x cheaper ($10.00 vs $20.00 per million).
Which is cheaper, Claude Opus 5.5 or GPT-5.1-Codex-Max?
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 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, Claude Opus 5.5 or GPT-5.1-Codex-Max?
Claude Opus 5.5, with 1M tokens against 400K.
How many benchmarks is the Claude Opus 5.5 vs GPT-5.1-Codex-Max comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Claude Opus 5.5's coding index rests on 5 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.