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Claude Opus 4.5 vs GPT-5.4

GPT-5.4 leads Claude Opus 4.5 on coding, 64.4 to 44.0 on the Vibe Coding Index, and GPT-5.4 costs 1.7x less per output token ($15.00 vs $25.00 per million). Updated October 22, 2026; 90 benchmarks have a result for both.

Replace Claude Opus 4.5 Replace GPT-5.4
Claude Opus 4.5Anthropic
Coding
44.0
Overall
55.7
Output $/M
$25.00
31
GPT-5.4OpenAI
Coding
64.4
Overall
69.6
Output $/M
$15.00
59
vs boards won of 90 shared

Claude Opus 4.5 or GPT-5.4: which to pick

Pick GPT-5.4 for coding: it scores 64.4 on the Vibe Coding Index against 44.0 for Claude Opus 4.5.

Pick Claude Opus 4.5 for work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Model AClaude Opus 4.5Anthropic44.0/1003 independent benchmarks$1.37 per solved taskModel BGPT-5.4OpenAI64.4/1003 independent benchmarks$1.02 per solved task
Shared results
90
Claude Opus 4.5 only
18
GPT-5.4 only
20
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 4.5 44.0 from 3 benchmarks, GPT-5.4 64.4 from 3 benchmarks.
Widest category
Math, 18.6 points apart on average over 7 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Opus 4.5 20.6% against GPT-5.4 67.4%, 46.8 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.5 $25.00 against GPT-5.4 $15.00 per million output tokens, 1.7x apart.
Context window
Claude Opus 4.5 takes 200K tokens, GPT-5.4 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 4.5BarsGPT-5.4Ties
Coding48
Intelligence02
Agentic work71
Reasoning212
Math07
Knowledge49
Web design80
General620
All shared boards3159
CodingLike-for-likeSix of these boards feed the Vibe Coding Index48
Coding benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
SWE-bench Verified79.2%Not measuredOnly Claude Opus 4.5 measured
SWE-bench (full test set)52.6%Not measuredOnly Claude Opus 4.5 measured
SWE-bench Multilingual70.7%Not measuredOnly Claude Opus 4.5 measured
LMArena WebDev14941464Claude Opus 4.5
AA Coding IndexNot measured71.1Only GPT-5.4 measured
LiveCodeBench (Vals AI)83.7%84.1%GPT-5.4
SWE-bench Verified (Vals AI)76.4%78.2%GPT-5.4
Vibe Code Bench (Vals AI)20.6%67.4%GPT-5.4
Code migration (Vals AI)Not measured35.0%Only GPT-5.4 measured
ProgramBench (Vals AI)Not measured0.5%Only GPT-5.4 measured
SkillsBench (Vals AI)Not measured51.7%Only GPT-5.4 measured
LiveCodeBench (Artificial Analysis run)87.1%Not measuredOnly Claude Opus 4.5 measured
Terminal-Bench Hard (Artificial Analysis run)47.0%57.6%GPT-5.4
Terminal-Bench63.1%81.8%GPT-5.4
GSO-Bench26.5%31.4%GPT-5.4
WeirdML63.7%77.7%GPT-5.4
MirrorCodeNot measured15.6%Only GPT-5.4 measured
Cybench82.0%Not measuredOnly Claude Opus 4.5 measured
ALE-BenchNot measured1607.0Only GPT-5.4 measured
LMArena Text: coding15031496Claude Opus 4.5
LMArena Text: software and IT14831491GPT-5.4
LMArena WebDev: React14781454Claude Opus 4.5
LMArena WebDev: HTML15101478Claude Opus 4.5
LMArena WebDev: from an imageNot measured1436Only GPT-5.4 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
AA Intelligence Index29.139.0GPT-5.4
Epoch Capabilities Index150.1157.3GPT-5.4
Agentic workLike-for-likePublic boards, shown as published, kept out of the index71
Agentic work benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
Design Arena: agents building web apps11591059Claude Opus 4.5
Design Arena: agents building full-stack apps11561017Claude Opus 4.5
Design Arena: agents building mobile apps11891087Claude Opus 4.5
Design Arena: agents building Android apps11761031Claude Opus 4.5
Design Arena: agents building Godot gamesNot measured1135Only GPT-5.4 measured
τ²-Bench Telecom89.5%87.1%Claude Opus 4.5
APEX-AgentsNot measured52.4%Only GPT-5.4 measured
METR time horizons75.0%74.3%Claude Opus 4.5
Remote Labor Index3.8%Not measuredOnly Claude Opus 4.5 measured
GDPval45.5%Not measuredOnly Claude Opus 4.5 measured
BALROG43.5%Not measuredOnly Claude Opus 4.5 measured
DeepResearch Bench54.8%35.1%Claude Opus 4.5
PostTrainBenchNot measured19.0%Only GPT-5.4 measured
OSWorld66.3%Not measuredOnly Claude Opus 4.5 measured
Vending-Bench 2$4,967$6,144GPT-5.4
Berkeley Function Calling Leaderboard (BFCL)77.5%Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index212
Reasoning benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
GPQA Diamond85.9%91.7%GPT-5.4
MMMU Pro (Vals AI)83.0%87.5%GPT-5.4
GPQA Diamond (Artificial Analysis run)86.6%92.0%GPT-5.4
Humanity's Last Exam (Artificial Analysis run)30.1%43.7%GPT-5.4
GPQA Diamond (Epoch AI run)86.0%93.3%GPT-5.4
ARC-AGI80.0%93.7%GPT-5.4
ARC-AGI-237.6%74.0%GPT-5.4
SimpleBench62.0%Not measuredOnly Claude Opus 4.5 measured
Chess puzzles14.0%48.0%GPT-5.4
Mystery game puzzles22.0%37.0%GPT-5.4
EBR-bench14.3%25.4%GPT-5.4
VPCT40.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: hard prompts14761485GPT-5.4
LMArena Text: expert14871507GPT-5.4
LMArena Text: hard prompts in English14821479Claude Opus 4.5
LMArena Vision: diagramsNot measured1327Only GPT-5.4 measured
LMArena Vision: homeworkNot measured1336Only GPT-5.4 measured
Kagi LLM Benchmark80.2%63.8%Claude Opus 4.5
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index07
Math benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
AIME95.4%96.7%GPT-5.4
MGSM (Vals AI)95.2%Not measuredOnly Claude Opus 4.5 measured
AA Math Index91.3Not measuredOnly Claude Opus 4.5 measured
AIME 2025 (Artificial Analysis run)91.3%Not measuredOnly Claude Opus 4.5 measured
OTIS Mock AIME86.1%97.8%GPT-5.4
FrontierMath, tiers 1 to 334.4%78.6%GPT-5.4
FrontierMath, tier 44.9%49.0%GPT-5.4
ProofBench36.0%56.0%GPT-5.4
LMArena Text: math14631488GPT-5.4
LMArena Text: mathematical work14681497GPT-5.4
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index49
Knowledge benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
MMLU Pro87.3%87.5%GPT-5.4
LegalBench (Vals AI)84.6%86.0%GPT-5.4
CaseLaw (Vals AI)62.6%63.8%GPT-5.4
CorpFin (Vals AI)65.1%65.3%GPT-5.4
TaxEval (Vals AI)74.9%74.0%Claude Opus 4.5
MortgageTax (Vals AI)68.7%68.3%Claude Opus 4.5
MedQA (Vals AI)95.9%96.1%GPT-5.4
MedCode (Vals AI)49.2%41.3%Claude Opus 4.5
MMLU Pro (Artificial Analysis run)89.5%Not measuredOnly Claude Opus 4.5 measured
SimpleQA Verified45.7%45.1%Claude Opus 4.5
GeoBench75.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: science14541479GPT-5.4
LMArena Text: medicine and healthcare14441458GPT-5.4
LMArena Text: legal and government14591486GPT-5.4
LMArena Text: business and finance14481474GPT-5.4
FACTS Benchmark Suite43.9%Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
Design Arena: websites12471198Claude Opus 4.5
Design Arena: UI components12351212Claude Opus 4.5
Design Arena: game dev12281194Claude Opus 4.5
Design Arena: data viz12431196Claude Opus 4.5
Design Arena: 3D12131065Claude Opus 4.5
Design Arena: all code categories12421179Claude Opus 4.5
Design Arena: SVG11801141Claude Opus 4.5
Design Arena: ASCII art11901188Claude Opus 4.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index620
General benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
SAGE (Vals AI)52.1%43.3%Claude Opus 4.5
MedScribe (Vals AI)85.3%77.5%Claude Opus 4.5
IFBench58.0%73.9%GPT-5.4
Long context reasoning (AA-LCR)77.3%82.0%GPT-5.4
DTBench89.9%94.4%GPT-5.4
LMCA44.5%52.0%GPT-5.4
CL-bench21.1%27.9%GPT-5.4
Furniture assembly28.3%37.5%GPT-5.4
CL-bench LifeNot measured21.7%Only GPT-5.4 measured
LMArena Text14511469GPT-5.4
LMArena Text: instruction following14781469Claude Opus 4.5
LMArena Text: creative writing14451439Claude Opus 4.5
LMArena VisionNot measured1303Only GPT-5.4 measured
LMArena Text: English14611467GPT-5.4
LMArena Text: non-English14381465GPT-5.4
LMArena Text: Chinese14701520GPT-5.4
LMArena Text: German14491472GPT-5.4
LMArena Text: Japanese14171485GPT-5.4
LMArena Text: Korean14241449GPT-5.4
LMArena Text: French14711493GPT-5.4
LMArena Text: Spanish14571452Claude Opus 4.5
LMArena Text: Russian14471480GPT-5.4
LMArena Text: Polish14391472GPT-5.4
LMArena Text: multi-turn14661482GPT-5.4
LMArena Text: longer queries14791473Claude Opus 4.5
LMArena Text: writing and language14521458GPT-5.4
LMArena Text: entertainment and media14341438GPT-5.4
LMArena Vision: EnglishNot measured1301Only GPT-5.4 measured
LMArena Vision: ChineseNot measured1354Only GPT-5.4 measured
LMArena Vision: reading textNot measured1312Only GPT-5.4 measured
LMArena Vision: humorNot measured1284Only GPT-5.4 measured
LMArena Vision: recognizing thingsNot measured1251Only GPT-5.4 measured
LMArena Vision: creative writingNot measured1283Only GPT-5.4 measured
LMArena Document14621471GPT-5.4
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.5 and GPT-5.4
BenchmarkClaude Opus 4.5GPT-5.4Leader
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 4.5$0.018Fits in one request
GPT-5.4$0.010Fits in one request

GPT-5.4 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.5$0.325Fits in one request
GPT-5.4$0.170Fits in one request

GPT-5.4 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.5$1.25Exceeds the context window
GPT-5.4$0.650Fits in one request

GPT-5.4 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 4.5 and GPT-5.4
SpecificationAnthropic Claude Opus 4.5OpenAI GPT-5.4
MakerAnthropicOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedNovember 24, 2025March 5, 2026
Context window200K1.05M
Input $/Mtok$5.00$2.50
Output $/Mtok$25.00$15.00
Coding index44.064.4
Independent measurements behind it33
Cost per solved task$1.37$1.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.5 better than GPT-5.4 for coding?

Pick GPT-5.4 for coding: it scores 64.4 on the Vibe Coding Index against 44.0 for Claude Opus 4.5. Pick Claude Opus 4.5 for work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Which is cheaper, Claude Opus 4.5 or GPT-5.4?

Claude Opus 4.5 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-5.4 costs $2.50 and $15.00. Per solved SWE-bench Verified task, Claude Opus 4.5 costs $1.37 and GPT-5.4 $1.02.

Which has the bigger context window, Claude Opus 4.5 or GPT-5.4?

GPT-5.4, with 1.05M tokens against 200K.

How many benchmarks is the Claude Opus 4.5 vs GPT-5.4 comparison based on?

90 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.5's coding index rests on 3 independent benchmarks and GPT-5.4's on 3. Where only one model has a result, the page says so instead of naming a winner.

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