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Claude Opus 4.8 vs GPT-6 Luna

Claude Opus 4.8 leads GPT-6 Luna on coding, 65.0 to 57.3 on the Vibe Coding Index, and GPT-6 Luna costs 50.0x less per output token ($0.50 vs $25.00 per million). Updated October 22, 2026; 91 benchmarks have a result for both.

Replace Claude Opus 4.8 Replace GPT-6 Luna
Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
73
GPT-6 LunaOpenAI
Coding
57.3
Overall
59.7
Output $/M
$0.50
16
vs boards won of 91 shared, 2 tied

Claude Opus 4.8 or GPT-6 Luna: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 57.3 for GPT-6 Luna.

Pick GPT-6 Luna for output tokens 50.0x cheaper ($0.50 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).

Model AClaude Opus 4.8Anthropic65.0/1006 independent benchmarks$2.17 per solved taskModel BGPT-6 LunaOpenAI57.3/1005 independent benchmarksNo cost per solved task
Shared results
91
Claude Opus 4.8 only
45
GPT-6 Luna only
13
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 4.8 65.0 from 6 benchmarks, GPT-6 Luna 57.3 from 5 benchmarks.
Widest category
Knowledge, 12.6 points apart on average over 7 shared benchmarks.
Widest single gap
LiveBench research: Claude Opus 4.8 81.8% against GPT-6 Luna 43.5%, 38.3 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against GPT-6 Luna $0.50 per million output tokens, 50.0x apart.
Context window
Claude Opus 4.8 takes 1M tokens, GPT-6 Luna 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 4.8BarsGPT-6 LunaTies
Coding76
Intelligence20
Agentic work1101 tie
Reasoning120
Math411 tie
Knowledge61
Web design45
General273
All shared boards73162 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index76
Coding benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
LiveBench coding77.3%84.5%GPT-6 Luna
LMArena WebDev15561578GPT-6 Luna
AA Coding Index74.3Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Vals AI)87.8%Not measuredOnly Claude Opus 4.8 measured
SWE-bench Verified (Vals AI)88.6%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 4 (Vals AI)23.2%13.6%Claude Opus 4.8
Vibe Code Bench (Vals AI)82.7%81.7%Claude Opus 4.8
Code migration (Vals AI)47.3%42.5%Claude Opus 4.8
ProgramBench (Vals AI)1.0%0.5%Claude Opus 4.8
IOI (Vals AI)Not measured55.6%Only GPT-6 Luna measured
Terminal-Bench 2.1 (Vals AI)71.9%73.0%GPT-6 Luna
SWE-bench Multimodal (Vals AI)Not measured37.5%Only GPT-6 Luna measured
SkillsBench (Vals AI)59.2%Not measuredOnly Claude Opus 4.8 measured
CyberBench (Vals AI)Not measured76.3%Only GPT-6 Luna measured
SciCode54.4%54.6%GPT-6 Luna
Terminal-Bench Hard (Artificial Analysis run)58.3%Not measuredOnly Claude Opus 4.8 measured
FrontierCode46.5%42.4%Claude Opus 4.8
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
ALE-BenchNot measured1576.9Only GPT-6 Luna measured
LMArena Text: coding14901437Claude Opus 4.8
LMArena Text: software and IT14881423Claude Opus 4.8
LMArena WebDev: React15571573GPT-6 Luna
LMArena WebDev: HTML15431595GPT-6 Luna
LMArena WebDev: from an imageNot measured1571Only GPT-6 Luna measured
SciCode12.3%Not measuredOnly Claude Opus 4.8 measured
SWE Atlas: Codebase QnA57.3%Not measuredOnly Claude Opus 4.8 measured
SWE Atlas: Refactoring46.7%Not measuredOnly Claude Opus 4.8 measured
SWE Atlas: Test Writing49.6%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
AA Intelligence Index41.838.1Claude Opus 4.8
Epoch Capabilities Index159.0156.8Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index110
Agentic work benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
AA Agentic Index41.9Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building web apps12331191Claude Opus 4.8
Design Arena: agents building full-stack apps12491158Claude Opus 4.8
Design Arena: agents building mobile apps12221131Claude Opus 4.8
Design Arena: agents building Android apps1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1160Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides1201Not measuredOnly Claude Opus 4.8 measured
Design Arena: spreadsheets1314Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%43.5%Claude Opus 4.8
LiveBench browser96.0%72.0%Claude Opus 4.8
LiveBench long agentic48.3%48.1%Claude Opus 4.8
SREBench (Vals AI)Not measured2.7%Only GPT-6 Luna measured
Finance Agent (Vals AI)53.9%49.9%Claude Opus 4.8
Tax Agent Bench (Vals AI)30.0%19.9%Claude Opus 4.8
Legal Research Bench (Vals AI)43.8%30.3%Claude Opus 4.8
Harvey's Legal Agent Benchmark (Vals AI)Not measured4.2%Only GPT-6 Luna measured
Excel Modeling Benchmark (Vals AI)69.4%68.5%Claude Opus 4.8
BioMysteryBench (Vals AI)Not measured61.5%Only GPT-6 Luna measured
Terminal-Bench-Science (Vals AI)4.3%4.3%Tie
Vals Science IndexNot measured28.4%Only GPT-6 Luna measured
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%Not measuredOnly Claude Opus 4.8 measured
APEX-Agents48.9%44.3%Claude Opus 4.8
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
SpireClimbNot measured0.0%Only GPT-6 Luna measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
MCP Atlas82.2%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 9 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index120
Reasoning benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
GPQA Diamond92.4%Not measuredOnly Claude Opus 4.8 measured
LiveBench reasoning89.2%81.8%Claude Opus 4.8
MysteryMechanism (Vals AI)Not measured19.4%Only GPT-6 Luna measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)92.0%Not measuredOnly Claude Opus 4.8 measured
Humanity's Last Exam (Artificial Analysis run)48.7%38.5%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%90.5%Claude Opus 4.8
ARC-AGI92.5%86.7%Claude Opus 4.8
ARC-AGI-272.1%59.3%Claude Opus 4.8
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%36.0%Claude Opus 4.8
Mystery game puzzles36.0%7.0%Claude Opus 4.8
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821410Claude Opus 4.8
LMArena Text: expert15031442Claude Opus 4.8
LMArena Text: hard prompts in English14871410Claude Opus 4.8
LMArena Vision: diagrams13151245Claude Opus 4.8
LMArena Vision: homework13371261Claude Opus 4.8
Kagi LLM Benchmark88.8%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index41
Math benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
OTIS Mock AIME98.3%98.9%GPT-6 Luna
FrontierMath, tiers 1 to 380.0%78.9%Claude Opus 4.8
FrontierMath, tier 456.1%56.1%Tie
ProofBench69.0%64.0%Claude Opus 4.8
LMArena Text: math14861409Claude Opus 4.8
LMArena Text: mathematical work14971427Claude Opus 4.8
MathArena39.8%Not measuredOnly Claude Opus 4.8 measured
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 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
MMLU Pro89.6%Not measuredOnly Claude Opus 4.8 measured
LegalBench (Vals AI)83.6%Not measuredOnly Claude Opus 4.8 measured
CorpFin (Vals AI)66.7%Not measuredOnly Claude Opus 4.8 measured
TaxEval (Vals AI)75.6%Not measuredOnly Claude Opus 4.8 measured
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedCode (Vals AI)53.2%44.7%Claude Opus 4.8
SimpleQA Verified53.0%41.4%Claude Opus 4.8
LMArena Text: science14771386Claude Opus 4.8
LMArena Text: medicine and healthcare14641352Claude Opus 4.8
LMArena Text: legal and government14771400Claude Opus 4.8
LMArena Text: business and finance14581388Claude Opus 4.8
FACTS Benchmark Suite53.5%63.3%GPT-6 Luna
PRBench LegalNot measured42.9%Only GPT-6 Luna measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index45
Web design benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
Design Arena: websites12581271GPT-6 Luna
Design Arena: UI components12551295GPT-6 Luna
Design Arena: game dev12641258Claude Opus 4.8
Design Arena: data viz12401217Claude Opus 4.8
Design Arena: 3D12221218Claude Opus 4.8
Design Arena: all code categories12551270GPT-6 Luna
Design Arena: SVG11941253GPT-6 Luna
Design Arena: ASCII art12771153Claude Opus 4.8
LiveBench design78.8%82.5%GPT-6 Luna
GeneralLike-for-likePublic boards, shown as published, kept out of the index273
General benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
Vals IndexNot measured52.3%Only GPT-6 Luna measured
LiveBench data analysis66.0%73.4%GPT-6 Luna
Public Benefits Bench (Vals AI)68.1%57.6%Claude Opus 4.8
SAGE (Vals AI)54.8%48.1%Claude Opus 4.8
MedScribe (Vals AI)85.8%83.7%Claude Opus 4.8
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%Not measuredOnly Claude Opus 4.8 measured
Long context reasoning (AA-LCR)77.7%83.3%GPT-6 Luna
DTBench94.9%90.1%Claude Opus 4.8
LMCA57.5%44.5%Claude Opus 4.8
Surface Evolver Bench87.5%Not measuredOnly Claude Opus 4.8 measured
Furniture assembly42.5%44.2%GPT-6 Luna
LMArena Text14611389Claude Opus 4.8
LMArena Text: instruction following14761408Claude Opus 4.8
LMArena Text: creative writing14541363Claude Opus 4.8
LMArena Vision12941216Claude Opus 4.8
LMArena Text: English14681393Claude Opus 4.8
LMArena Text: non-English14501381Claude Opus 4.8
LMArena Text: Chinese15061427Claude Opus 4.8
LMArena Text: German14721376Claude Opus 4.8
LMArena Text: Japanese14421369Claude Opus 4.8
LMArena Text: Korean14311359Claude Opus 4.8
LMArena Text: French14811408Claude Opus 4.8
LMArena Text: Spanish14651391Claude Opus 4.8
LMArena Text: Russian14741392Claude Opus 4.8
LMArena Text: Polish14591383Claude Opus 4.8
LMArena Text: multi-turn14761392Claude Opus 4.8
LMArena Text: longer queries14831408Claude Opus 4.8
LMArena Text: writing and language14611384Claude Opus 4.8
LMArena Text: entertainment and media14401364Claude Opus 4.8
LMArena Vision: English12931204Claude Opus 4.8
LMArena Vision: Chinese13461266Claude Opus 4.8
LMArena Vision: reading text13031225Claude Opus 4.8
LMArena Vision: humor1282Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: creative writing13011205Claude Opus 4.8
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
EQ-Bench 41281Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and GPT-6 Luna
BenchmarkClaude Opus 4.8GPT-6 LunaLeader
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 4.8$0.018Fits in one request
GPT-6 Luna$0.0003Fits in one request

GPT-6 Luna costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
GPT-6 Luna$0.0065Fits in one request

GPT-6 Luna costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
GPT-6 Luna$0.025Fits in one request

GPT-6 Luna 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 4.8 and GPT-6 Luna
SpecificationAnthropic Claude Opus 4.8OpenAI GPT-6 Luna
MakerAnthropicOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedMay 27, 2026September 22, 2026
Context window1M1.05M
Input $/Mtok$5.00$0.10
Output $/Mtok$25.00$0.50
Coding index65.057.3
Independent measurements behind it65
Cost per solved task$2.17Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than GPT-6 Luna for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 57.3 for GPT-6 Luna. Pick GPT-6 Luna for output tokens 50.0x cheaper ($0.50 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).

Which is cheaper, Claude Opus 4.8 or GPT-6 Luna?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. Cost per solved task is known for Claude Opus 4.8 only.

Which has the bigger context window, Claude Opus 4.8 or GPT-6 Luna?

GPT-6 Luna, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs GPT-6 Luna comparison based on?

91 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.8's coding index rests on 6 independent benchmarks and GPT-6 Luna's on 5. Where only one model has a result, the page says so instead of naming a winner.

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