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Claude Opus 5.5 vs GPT-5.5

Claude Opus 5.5 leads GPT-5.5 on coding, 88.8 to 71.3 on the Vibe Coding Index, and Claude Opus 5.5 costs 1.5x less per output token ($20.00 vs $30.00 per million). Updated October 21, 2026; 91 benchmarks have a result for both.

Replace Claude Opus 5.5 Replace GPT-5.5
Claude Opus 5.5Anthropic
Coding
88.8
Overall
87.1
Output $/M
$20.00
87
GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
4
vs boards won of 91 shared

Claude Opus 5.5 or GPT-5.5: which to pick

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 71.3 for GPT-5.5.

Pick GPT-5.5 for a larger context window (1.05M against 1M tokens) and work measured by GPQA Diamond (Epoch AI run) or FACTS Benchmark Suite, where it leads.

Model AClaude Opus 5.5Anthropic88.8/1005 independent benchmarksNo cost per solved taskModel BGPT-5.5OpenAI71.3/1005 independent benchmarks$1.65 per solved task
Shared results
91
Claude Opus 5.5 only
18
GPT-5.5 only
43
Like-for-like categories
8 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.

At a glance

Coding index
Claude Opus 5.5 88.8 from 5 benchmarks, GPT-5.5 71.3 from 5 benchmarks.
Widest category
Agentic work, 25.0 points apart on average over 14 shared benchmarks.
Widest single gap
Time Horizon Index (Vals AI): Claude Opus 5.5 91.3% against GPT-5.5 8.3%, 83.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 5.5 $20.00 against GPT-5.5 $30.00 per million output tokens, 1.5x apart.
Context window
Claude Opus 5.5 takes 1M tokens, GPT-5.5 1.05M.

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.

Boards won, where both have a result
CategoryClaude Opus 5.5BarsGPT-5.5Ties
Coding150
Intelligence20
Agentic work140
Reasoning121
Math60
Knowledge61
Web design80
General242
All shared boards874
CodingLike-for-likeSix of these boards feed the Vibe Coding Index150
Coding benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
LiveBench coding96.3%85.1%Claude Opus 5.5
LMArena WebDev18071513Claude Opus 5.5
AA Coding IndexNot measured74.9Only GPT-5.5 measured
LiveCodeBench (Vals AI)Not measured85.3%Only GPT-5.5 measured
SWE-bench Verified (Vals AI)Not measured82.6%Only GPT-5.5 measured
Terminal-Bench 4 (Vals AI)65.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench (Vals AI)90.3%69.8%Claude Opus 5.5
Code migration (Vals AI)66.7%45.2%Claude Opus 5.5
ProgramBench (Vals AI)18.5%0.5%Claude Opus 5.5
IOI (Vals AI)95.1%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench 2.1 (Vals AI)87.6%76.4%Claude Opus 5.5
SWE-bench Multimodal (Vals AI)70.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench 1-100 (Vals AI)30.4%Not measuredOnly Claude Opus 5.5 measured
SkillsBench (Vals AI)Not measured62.5%Only GPT-5.5 measured
CyberBench (Vals AI)74.6%Not measuredOnly Claude Opus 5.5 measured
SciCode66.9%56.1%Claude Opus 5.5
Terminal-Bench Hard (Artificial Analysis run)Not measured60.6%Only GPT-5.5 measured
Terminal-BenchNot measured84.7%Only GPT-5.5 measured
FrontierCode54.6%43.0%Claude Opus 5.5
FrontierSWE62.3%Not measuredOnly Claude Opus 5.5 measured
GSO-BenchNot measured40.2%Only GPT-5.5 measured
WeirdMLNot measured84.9%Only GPT-5.5 measured
MirrorCode77.4%10.0%Claude Opus 5.5
ALE-Bench2147.41943.0Claude Opus 5.5
LMArena Text: coding15451494Claude Opus 5.5
LMArena Text: software and IT15381493Claude Opus 5.5
LMArena WebDev: React18551506Claude Opus 5.5
LMArena WebDev: HTML17531543Claude Opus 5.5
LMArena WebDev: from an image17531532Claude Opus 5.5
SciCode18.5%Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 9 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
AA Intelligence Index57.638.4Claude Opus 5.5
Epoch Capabilities Index168.8159.7Claude Opus 5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index140
Agentic work benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
AA Agentic IndexNot measured36.4Only GPT-5.5 measured
Design Arena: agents building web apps13171117Claude Opus 5.5
Design Arena: agents building full-stack appsNot measured1089Only GPT-5.5 measured
Design Arena: agents building mobile apps13101143Claude Opus 5.5
Design Arena: agents building Android appsNot measured1163Only GPT-5.5 measured
Design Arena: agents building Godot gamesNot measured1173Only GPT-5.5 measured
Design Arena: agents building gamesNot measured1179Only GPT-5.5 measured
Design Arena: HTML slidesNot measured1067Only GPT-5.5 measured
Design Arena: PowerPoint slidesNot measured1109Only GPT-5.5 measured
Design Arena: spreadsheets1352Not measuredOnly Claude Opus 5.5 measured
LiveBench research85.0%61.6%Claude Opus 5.5
LiveBench browser80.0%48.0%Claude Opus 5.5
LiveBench long agentic85.0%44.6%Claude Opus 5.5
SREBench (Vals AI)33.6%3.8%Claude Opus 5.5
Finance Agent (Vals AI)58.6%51.8%Claude Opus 5.5
Tax Agent Bench (Vals AI)45.6%21.8%Claude Opus 5.5
Legal Research Bench (Vals AI)50.5%40.4%Claude Opus 5.5
Harvey's Legal Agent Benchmark (Vals AI)9.2%Not measuredOnly Claude Opus 5.5 measured
Excel Modeling Benchmark (Vals AI)75.9%64.5%Claude Opus 5.5
BioMysteryBench (Vals AI)79.3%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench-Science (Vals AI)47.1%Not measuredOnly Claude Opus 5.5 measured
Vals Science Index58.7%Not measuredOnly Claude Opus 5.5 measured
Time Horizon Index (Vals AI)91.3%8.3%Claude Opus 5.5
CUA-bench (Vals AI)14.0%Not measuredOnly Claude Opus 5.5 measured
Robo-bench (Vals AI)14.6%Not measuredOnly Claude Opus 5.5 measured
τ²-Bench TelecomNot measured93.9%Only GPT-5.5 measured
APEX-Agents73.5%55.1%Claude Opus 5.5
Remote Labor Index21.3%6.3%Claude Opus 5.5
OSWorld 2.0Not measured13.0%Only GPT-5.5 measured
DeepResearch BenchNot measured54.0%Only GPT-5.5 measured
PostTrainBenchNot measured27.2%Only GPT-5.5 measured
SpireClimb3.3%Not measuredOnly Claude Opus 5.5 measured
Vending-Bench 2$9,235$7,524Claude Opus 5.5
LMArena Search1213Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 7 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index121
Reasoning benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
GPQA DiamondNot measured93.2%Only GPT-5.5 measured
LiveBench reasoning92.2%89.7%Claude Opus 5.5
MysteryMechanism (Vals AI)49.5%Not measuredOnly Claude Opus 5.5 measured
MMMU Pro (Vals AI)Not measured88.3%Only GPT-5.5 measured
GPQA Diamond (Artificial Analysis run)Not measured93.5%Only GPT-5.5 measured
Humanity's Last Exam (Artificial Analysis run)61.4%45.8%Claude Opus 5.5
GPQA Diamond (Epoch AI run)90.6%90.7%GPT-5.5
ARC-AGI98.5%95.0%Claude Opus 5.5
ARC-AGI-293.3%85.0%Claude Opus 5.5
SimpleBenchNot measured69.0%Only GPT-5.5 measured
Chess puzzles67.0%63.0%Claude Opus 5.5
Mystery game puzzles71.0%56.0%Claude Opus 5.5
EBR-bench71.4%34.3%Claude Opus 5.5
LMArena Text: hard prompts15361489Claude Opus 5.5
LMArena Text: expert15491507Claude Opus 5.5
LMArena Text: hard prompts in English15351483Claude Opus 5.5
LMArena Vision: diagrams13451325Claude Opus 5.5
LMArena Vision: homework13621332Claude Opus 5.5
Kagi LLM BenchmarkNot measured88.8%Only GPT-5.5 measured
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
OTIS Mock AIME100.0%84.4%Claude Opus 5.5
FrontierMath, tiers 1 to 391.2%85.3%Claude Opus 5.5
FrontierMath, tier 495.0%72.5%Claude Opus 5.5
ProofBench100.0%50.0%Claude Opus 5.5
LMArena Text: math15181487Claude Opus 5.5
LMArena Text: mathematical work15161496Claude Opus 5.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
Knowledge benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
MMLU ProNot measured88.1%Only GPT-5.5 measured
LegalBench (Vals AI)Not measured86.5%Only GPT-5.5 measured
CaseLaw (Vals AI)Not measured66.2%Only GPT-5.5 measured
CorpFin (Vals AI)Not measured68.4%Only GPT-5.5 measured
TaxEval (Vals AI)Not measured75.0%Only GPT-5.5 measured
MortgageTax (Vals AI)Not measured68.8%Only GPT-5.5 measured
MedCode (Vals AI)49.8%49.1%Claude Opus 5.5
SimpleQA Verified72.2%63.0%Claude Opus 5.5
LMArena Text: science15241485Claude Opus 5.5
LMArena Text: medicine and healthcare15091465Claude Opus 5.5
LMArena Text: legal and government15181491Claude Opus 5.5
LMArena Text: business and finance14941478Claude Opus 5.5
FACTS Benchmark Suite65.3%66.7%GPT-5.5
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
Design Arena: websites13361256Claude Opus 5.5
Design Arena: UI components13921260Claude Opus 5.5
Design Arena: game dev14581294Claude Opus 5.5
Design Arena: data viz13971265Claude Opus 5.5
Design Arena: 3D14771198Claude Opus 5.5
Design Arena: all code categories13901260Claude Opus 5.5
Design Arena: SVG13331234Claude Opus 5.5
Design Arena: ASCII artNot measured1255Only GPT-5.5 measured
LiveBench design86.9%70.3%Claude Opus 5.5
GeneralLike-for-likePublic boards, shown as published, kept out of the index242
General benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
Vals Index70.2%Not measuredOnly Claude Opus 5.5 measured
LiveBench data analysis80.3%81.6%GPT-5.5
Public Benefits Bench (Vals AI)70.6%60.9%Claude Opus 5.5
SAGE (Vals AI)45.8%51.5%GPT-5.5
MedScribe (Vals AI)91.4%86.9%Claude Opus 5.5
Vals Multimodal IndexNot measured68.1%Only GPT-5.5 measured
IFBenchNot measured75.9%Only GPT-5.5 measured
Long context reasoning (AA-LCR)84.7%84.3%Claude Opus 5.5
DTBench98.9%96.0%Claude Opus 5.5
LMCA68.2%54.3%Claude Opus 5.5
Surface Evolver BenchNot measured88.1%Only GPT-5.5 measured
Furniture assembly83.3%44.2%Claude Opus 5.5
ExploitBenchNot measured47.4%Only GPT-5.5 measured
CL-bench LifeNot measured22.2%Only GPT-5.5 measured
LMArena Text15161471Claude Opus 5.5
LMArena Text: instruction following15371478Claude Opus 5.5
LMArena Text: creative writing15351455Claude Opus 5.5
LMArena Vision13211297Claude Opus 5.5
LMArena Text: English15191470Claude Opus 5.5
LMArena Text: non-English15071467Claude Opus 5.5
LMArena Text: Chinese15821534Claude Opus 5.5
LMArena Text: GermanNot measured1480Only GPT-5.5 measured
LMArena Text: Japanese15341499Claude Opus 5.5
LMArena Text: KoreanNot measured1460Only GPT-5.5 measured
LMArena Text: French14931485Claude Opus 5.5
LMArena Text: Spanish15081468Claude Opus 5.5
LMArena Text: Russian15171473Claude Opus 5.5
LMArena Text: PolishNot measured1465Only GPT-5.5 measured
LMArena Text: multi-turn15011476Claude Opus 5.5
LMArena Text: longer queries15321484Claude Opus 5.5
LMArena Text: writing and language15321466Claude Opus 5.5
LMArena Text: entertainment and media15151449Claude Opus 5.5
LMArena Vision: English13171292Claude Opus 5.5
LMArena Vision: ChineseNot measured1360Only GPT-5.5 measured
LMArena Vision: reading text13261306Claude Opus 5.5
LMArena Vision: humorNot measured1293Only GPT-5.5 measured
LMArena Vision: recognizing thingsNot measured1231Only GPT-5.5 measured
LMArena Vision: creative writing13201301Claude Opus 5.5
LMArena DocumentNot measured1486Only GPT-5.5 measured
Neither model has a result on the other 7 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 5.5 and GPT-5.5
BenchmarkClaude Opus 5.5GPT-5.5Leader
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-5.5$0.020Fits in one request

Claude Opus 5.5 costs less

Repository review

50K input + 3K output tokens

Claude Opus 5.5$0.260Fits in one request
GPT-5.5$0.340Fits in one request

Claude Opus 5.5 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 5.5$1.00Fits in one request
GPT-5.5$1.30Fits in one request

Claude Opus 5.5 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.

Specifications of Claude Opus 5.5 and GPT-5.5
SpecificationAnthropic Claude Opus 5.5OpenAI GPT-5.5
MakerAnthropicOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 22, 2026April 24, 2026
Context window1M1.05M
Input $/Mtok$4.00$5.00
Output $/Mtok$20.00$30.00
Coding index88.871.3
Independent measurements behind it55
Cost per solved taskNot computable$1.65
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 5.5 better than GPT-5.5 for coding?

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 71.3 for GPT-5.5. Pick GPT-5.5 for a larger context window (1.05M against 1M tokens) and work measured by GPQA Diamond (Epoch AI run) or FACTS Benchmark Suite, where it leads.

Which is cheaper, Claude Opus 5.5 or GPT-5.5?

Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Cost per solved task is known for GPT-5.5 only.

Which has the bigger context window, Claude Opus 5.5 or GPT-5.5?

GPT-5.5, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 5.5 vs GPT-5.5 comparison based on?

91 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-5.5's on 5. Where only one model has a result, the page says so instead of naming a winner.

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