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Claude Fable 5.1 vs GPT-5.6 Luna

Claude Fable 5.1 leads GPT-5.6 Luna on coding, 84.2 to 58.0 on the Vibe Coding Index, and GPT-5.6 Luna costs 41.7x less per output token ($1.20 vs $50.00 per million). Updated October 22, 2026; 106 benchmarks have a result for both.

Replace Claude Fable 5.1 Replace GPT-5.6 Luna
Claude Fable 5.1Anthropic
Coding
84.2
Overall
84.7
Output $/M
$50.00
104
GPT-5.6 LunaOpenAI
Coding
58.0
Overall
61.6
Output $/M
$1.20
2
vs boards won of 106 shared

Claude Fable 5.1 or GPT-5.6 Luna: which to pick

Pick Claude Fable 5.1 for coding: it scores 84.2 on the Vibe Coding Index against 58.0 for GPT-5.6 Luna, though on 5 benchmarks against 6.

Pick GPT-5.6 Luna for output tokens 41.7x cheaper ($1.20 vs $50.00 per million) and a larger context window (1.05M against 1M tokens).

Model AClaude Fable 5.1Anthropic84.2/1005 independent benchmarksNo cost per solved taskModel BGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task
Shared results
106
Claude Fable 5.1 only
27
GPT-5.6 Luna only
14
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 Fable 5.1 84.2 from 5 benchmarks, GPT-5.6 Luna 58.0 from 6 benchmarks.
Widest category
Agentic work, 23.4 points apart on average over 12 shared benchmarks.
Widest single gap
Terminal-Bench 4 (Vals AI): Claude Fable 5.1 58.1% against GPT-5.6 Luna 11.6%, 61.9 points apart on a 0 to 100 scale.
Output price
Claude Fable 5.1 $50.00 against GPT-5.6 Luna $1.20 per million output tokens, 41.7x apart.
Context window
Claude Fable 5.1 takes 1M tokens, GPT-5.6 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 Fable 5.1BarsGPT-5.6 LunaTies
Coding201
Intelligence20
Agentic work120
Reasoning150
Math60
Knowledge91
Web design90
General310
All shared boards1042
CodingLike-for-likeSix of these boards feed the Vibe Coding Index201
Coding benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
LiveBench coding97.7%73.6%Claude Fable 5.1
LMArena WebDev17431518Claude Fable 5.1
AA Coding Index81.671.4Claude Fable 5.1
LiveCodeBench (Vals AI)90.5%Not measuredOnly Claude Fable 5.1 measured
SWE-bench Verified (Vals AI)Not measured93.0%Only GPT-5.6 Luna measured
Terminal-Bench 4 (Vals AI)58.1%11.6%Claude Fable 5.1
Vibe Code Bench (Vals AI)90.3%77.1%Claude Fable 5.1
Code migration (Vals AI)54.6%44.5%Claude Fable 5.1
ProgramBench (Vals AI)7.0%0.0%Claude Fable 5.1
IOI (Vals AI)90.8%61.8%Claude Fable 5.1
Terminal-Bench 2.1 (Vals AI)85.0%79.0%Claude Fable 5.1
SWE-bench Multimodal (Vals AI)61.3%Not measuredOnly Claude Fable 5.1 measured
Vibe Code Bench 1-100 (Vals AI)28.0%22.6%Claude Fable 5.1
SkillsBench (Vals AI)61.5%60.5%Claude Fable 5.1
CyberBench (Vals AI)70.4%73.6%GPT-5.6 Luna
SciCode63.1%53.6%Claude Fable 5.1
FrontierCode50.9%39.8%Claude Fable 5.1
FrontierSWE56.3%Not measuredOnly Claude Fable 5.1 measured
GSO-Bench88.2%Not measuredOnly Claude Fable 5.1 measured
WeirdML92.9%60.9%Claude Fable 5.1
MirrorCode73.3%Not measuredOnly Claude Fable 5.1 measured
ALE-Bench2143.21667.4Claude Fable 5.1
LMArena Text: coding15321466Claude Fable 5.1
LMArena Text: software and IT15301463Claude Fable 5.1
LMArena WebDev: React17921508Claude Fable 5.1
LMArena WebDev: HTML16841520Claude Fable 5.1
LMArena WebDev: from an image17221517Claude Fable 5.1
SciCodeNot measured6.2%Only GPT-5.6 Luna measured
SWE-Bench Pro V299.1%Not measuredOnly Claude Fable 5.1 measured
SWE Atlas: Codebase QnA60.0%Not measuredOnly Claude Fable 5.1 measured
SWE Atlas: Refactoring56.7%Not measuredOnly Claude Fable 5.1 measured
SWE Atlas: Test Writing67.0%Not measuredOnly Claude Fable 5.1 measured
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
AA Intelligence Index53.437.3Claude Fable 5.1
Epoch Capabilities Index166.5156.5Claude Fable 5.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index120
Agentic work benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
AA Agentic Index57.942.1Claude Fable 5.1
Design Arena: agents building web apps1318Not measuredOnly Claude Fable 5.1 measured
Design Arena: agents building full-stack apps1326Not measuredOnly Claude Fable 5.1 measured
Design Arena: agents building mobile apps1267Not measuredOnly Claude Fable 5.1 measured
Design Arena: agents building Godot games1327Not measuredOnly Claude Fable 5.1 measured
Design Arena: PowerPoint slides1307Not measuredOnly Claude Fable 5.1 measured
Design Arena: spreadsheets1394Not measuredOnly Claude Fable 5.1 measured
LiveBench research82.0%51.0%Claude Fable 5.1
LiveBench browser100.0%68.0%Claude Fable 5.1
LiveBench long agentic80.8%30.4%Claude Fable 5.1
SREBench (Vals AI)22.9%1.5%Claude Fable 5.1
Finance Agent (Vals AI)58.9%55.0%Claude Fable 5.1
Tax Agent Bench (Vals AI)49.2%24.8%Claude Fable 5.1
Legal Research Bench (Vals AI)55.3%36.5%Claude Fable 5.1
Excel Modeling Benchmark (Vals AI)76.7%67.1%Claude Fable 5.1
BioMysteryBench (Vals AI)Not measured61.5%Only GPT-5.6 Luna measured
Terminal-Bench-Science (Vals AI)40.0%0.0%Claude Fable 5.1
Vals Science IndexNot measured25.3%Only GPT-5.6 Luna measured
Time Horizon Index (Vals AI)63.3%Not measuredOnly Claude Fable 5.1 measured
CUA-bench (Vals AI)13.2%Not measuredOnly Claude Fable 5.1 measured
Robo-bench (Vals AI)5.8%Not measuredOnly Claude Fable 5.1 measured
APEX-Agents68.6%43.0%Claude Fable 5.1
Remote Labor Index17.9%Not measuredOnly Claude Fable 5.1 measured
BALROGNot measured45.6%Only GPT-5.6 Luna measured
SpireClimb2.0%Not measuredOnly Claude Fable 5.1 measured
Vending-Bench 2$5,422$4,095Claude Fable 5.1
LMArena Search1246Not measuredOnly Claude Fable 5.1 measured
MCP Atlas87.2%Not measuredOnly Claude Fable 5.1 measured
Neither model has a result on the other 14 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index150
Reasoning benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
GPQA Diamond93.4%91.7%Claude Fable 5.1
LiveBench reasoning91.7%85.6%Claude Fable 5.1
MysteryMechanism (Vals AI)47.8%14.4%Claude Fable 5.1
MMMU Pro (Vals AI)90.6%85.0%Claude Fable 5.1
GPQA Diamond (Artificial Analysis run)93.7%91.1%Claude Fable 5.1
Humanity's Last Exam (Artificial Analysis run)59.1%39.5%Claude Fable 5.1
GPQA Diamond (Epoch AI run)Not measured91.6%Only GPT-5.6 Luna measured
ARC-AGI97.5%88.0%Claude Fable 5.1
ARC-AGI-290.0%59.5%Claude Fable 5.1
SimpleBenchNot measured46.8%Only GPT-5.6 Luna measured
Chess puzzles48.0%43.0%Claude Fable 5.1
Mystery game puzzles58.0%21.0%Claude Fable 5.1
EBR-bench57.1%Not measuredOnly Claude Fable 5.1 measured
LMArena Text: hard prompts15281451Claude Fable 5.1
LMArena Text: expert15441478Claude Fable 5.1
LMArena Text: hard prompts in English15221460Claude Fable 5.1
LMArena Vision: diagrams13431273Claude Fable 5.1
LMArena Vision: homework13451282Claude Fable 5.1
Kagi LLM BenchmarkNot measured49.1%Only GPT-5.6 Luna measured
Humanity's Last Exam (Scale run)51.3%Not measuredOnly Claude Fable 5.1 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 Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
OTIS Mock AIME100.0%98.3%Claude Fable 5.1
FrontierMath, tiers 1 to 390.2%82.1%Claude Fable 5.1
FrontierMath, tier 487.8%61.0%Claude Fable 5.1
ProofBench100.0%60.0%Claude Fable 5.1
LMArena Text: math15311459Claude Fable 5.1
LMArena Text: mathematical work15411470Claude Fable 5.1
MathArena78.1%Not measuredOnly Claude Fable 5.1 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index91
Knowledge benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
MMLU Pro92.4%86.0%Claude Fable 5.1
LegalBench (Vals AI)88.5%84.0%Claude Fable 5.1
CorpFin (Vals AI)Not measured64.2%Only GPT-5.6 Luna measured
TaxEval (Vals AI)76.0%76.2%GPT-5.6 Luna
MortgageTax (Vals AI)70.8%67.3%Claude Fable 5.1
MedCode (Vals AI)53.5%42.4%Claude Fable 5.1
SimpleQA Verified70.8%41.0%Claude Fable 5.1
LMArena Text: science15321433Claude Fable 5.1
LMArena Text: medicine and healthcare15311399Claude Fable 5.1
LMArena Text: legal and government15141446Claude Fable 5.1
LMArena Text: business and finance14931439Claude Fable 5.1
FACTS Benchmark SuiteNot measured35.0%Only GPT-5.6 Luna measured
PRBench Finance50.8%Not measuredOnly Claude Fable 5.1 measured
PRBench Legal51.6%Not measuredOnly Claude Fable 5.1 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index90
Web design benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
Design Arena: websites13121255Claude Fable 5.1
Design Arena: UI components13361248Claude Fable 5.1
Design Arena: game dev13811195Claude Fable 5.1
Design Arena: data viz13451212Claude Fable 5.1
Design Arena: 3D13921121Claude Fable 5.1
Design Arena: all code categories13351230Claude Fable 5.1
Design Arena: SVG13001193Claude Fable 5.1
Design Arena: ASCII art13231142Claude Fable 5.1
LiveBench design83.4%76.0%Claude Fable 5.1
GeneralLike-for-likePublic boards, shown as published, kept out of the index310
General benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 LunaLeader
LiveBench data analysis80.3%78.0%Claude Fable 5.1
Public Benefits Bench (Vals AI)74.9%61.2%Claude Fable 5.1
SAGE (Vals AI)48.5%44.2%Claude Fable 5.1
MedScribe (Vals AI)91.3%84.4%Claude Fable 5.1
Vals Multimodal IndexNot measured69.1%Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)85.3%83.7%Claude Fable 5.1
DTBench97.6%89.1%Claude Fable 5.1
LMCA65.5%48.5%Claude Fable 5.1
Surface Evolver BenchNot measured61.9%Only GPT-5.6 Luna measured
Furniture assembly70.0%42.5%Claude Fable 5.1
LMArena Text15121431Claude Fable 5.1
LMArena Text: instruction following15181437Claude Fable 5.1
LMArena Text: creative writing15091396Claude Fable 5.1
LMArena Vision13191257Claude Fable 5.1
LMArena Text: English15061441Claude Fable 5.1
LMArena Text: non-English15081417Claude Fable 5.1
LMArena Text: Chinese15841470Claude Fable 5.1
LMArena Text: German14991455Claude Fable 5.1
LMArena Text: Japanese15621415Claude Fable 5.1
LMArena Text: Korean15171415Claude Fable 5.1
LMArena Text: French15231458Claude Fable 5.1
LMArena Text: Spanish15201446Claude Fable 5.1
LMArena Text: Russian15201427Claude Fable 5.1
LMArena Text: Polish15251405Claude Fable 5.1
LMArena Text: multi-turn14931434Claude Fable 5.1
LMArena Text: longer queries15241436Claude Fable 5.1
LMArena Text: writing and language15101419Claude Fable 5.1
LMArena Text: entertainment and media14971402Claude Fable 5.1
LMArena Vision: English13131263Claude Fable 5.1
LMArena Vision: Chinese13911294Claude Fable 5.1
LMArena Vision: reading text13271264Claude Fable 5.1
LMArena Vision: humor13181190Claude Fable 5.1
LMArena Vision: creative writing13301257Claude Fable 5.1
LMArena DocumentNot measured1457Only GPT-5.6 Luna measured
EQ-Bench 4Not measured1156Only GPT-5.6 Luna measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Fable 5.1 and GPT-5.6 Luna
BenchmarkClaude Fable 5.1GPT-5.6 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 Fable 5.1$0.035Fits in one request
GPT-5.6 Luna$0.0008Fits in one request

GPT-5.6 Luna costs less

Repository review

50K input + 3K output tokens

Claude Fable 5.1$0.650Fits in one request
GPT-5.6 Luna$0.014Fits in one request

GPT-5.6 Luna costs less

Agent loop

200K input + 10K output tokens

Claude Fable 5.1$2.50Fits in one request
GPT-5.6 Luna$0.052Fits in one request

GPT-5.6 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 Fable 5.1 and GPT-5.6 Luna
SpecificationAnthropic Claude Fable 5.1OpenAI GPT-5.6 Luna
MakerAnthropicOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 1, 2026July 9, 2026
Context window1M1.05M
Input $/Mtok$10.00$0.20
Output $/Mtok$50.00$1.20
Coding index84.258.0
Independent measurements behind it56
Cost per solved taskNot computable$0.04
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Fable 5.1 better than GPT-5.6 Luna for coding?

Pick Claude Fable 5.1 for coding: it scores 84.2 on the Vibe Coding Index against 58.0 for GPT-5.6 Luna, though on 5 benchmarks against 6. Pick GPT-5.6 Luna for output tokens 41.7x cheaper ($1.20 vs $50.00 per million) and a larger context window (1.05M against 1M tokens).

Which is cheaper, Claude Fable 5.1 or GPT-5.6 Luna?

Claude Fable 5.1 costs $10.00 per million input tokens and $50.00 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Cost per solved task is known for GPT-5.6 Luna only.

Which has the bigger context window, Claude Fable 5.1 or GPT-5.6 Luna?

GPT-5.6 Luna, with 1.05M tokens against 1M.

How many benchmarks is the Claude Fable 5.1 vs GPT-5.6 Luna comparison based on?

106 benchmarks have a result for both models as of October 22, 2026. Claude Fable 5.1's coding index rests on 5 independent benchmarks and GPT-5.6 Luna's on 6. Where only one model has a result, the page says so instead of naming a winner.

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