ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Claude Fable 5.1 vs GPT-6 Luna

GPT-6 Luna comes out ahead, 75 to 61 on our weighted score, and it is the cheaper option too.

  1. Anthropic

    Claude Fable 5.1

    Released Sep 1, 2026

    61/100
    • ECI164.8
    • Price$10.00 / $50.00
    • Context1M
    Full specs Remove Claude Fable 5.1
  2. Our pick

    OpenAI

    GPT-6 Luna

    Released Sep 22, 2026

    75/100
    • ECI—
    • Price$0.10 / $0.50
    • Context1.05M
    Full specs Remove GPT-6 Luna

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-6 Luna is our pick

GPT-6 Luna is the better all-round choice, scoring 75/100 against Claude Fable 5.1 (61). It leads on price. Claude Fable 5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.

  • CapabilityClaude Fable 5.1Shared benchmarks: Claude Fable 5.1 87.0% · GPT-6 Luna 73.1%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · Claude Fable 5.1 $20.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · Claude Fable 5.1 1,000,000 tokens
  • Widest inputsSame inputsClaude Fable 5.1: Text, Images, PDFs · GPT-6 Luna: Text, Images, PDFs
  • Self-hostingNo open weightsBoth are available only through APIs
How the score is built
MeasureWeightClaude Fable 5.1GPT-6 Luna
CapabilityShared benchmarks50%8773
Price25%083
Inputs & features15%8080
Context window10%6061
Overall100%61/10075/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Claude Fable 5.1 vs GPT-6 Luna specifications side by side
SpecificationClaude Fable 5.1AnthropicGPT-6 LunaOpenAI
Capability
Capabilities Index (ECI)164.8—
ECI rank#4 of 148—
GPQA DiamondGraduate-level science questions—90.5%
FrontierMath Tiers 1–3Research-level mathematics90.2% (best)79.0%
OTIS Mock AIME 2024–2025Competition mathematics100% (best)98.9%
SimpleQA VerifiedShort factual questions70.8% (best)41.4%
Price per million tokens
Input$10.00$0.10 (best)
Output$50.00$0.50 (best)
Cached input$0.25$0.01 (best)
Blended (3:1)$20.00$0.20 (best)
Long-context rateSame rateOver 272K: $0.20 / $0.75
Price sourceOfficial Anthropic APIOfficial OpenAI API
Limits
Context window1,000,000 tokens1,050,000 tokens (best)
Max output128,000 tokens128,000 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesYes
AudioNoNo
VideoNoNo
ReasoningYeslow · medium · high · xhigh · maxYeslow · medium · high · xhigh · max
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryProprietary
API model IDclaude-fable-5-1gpt-6-luna
API providers29 (best)24
ReleasedSep 1, 2026Sep 22, 2026
Knowledge cutoffJun 2026May 18, 2026
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Claude Fable 5.1$200.00
  • GPT-6 Luna$2.00
04 — Questions

Which should you choose?

Which is better: Claude Fable 5.1 or GPT-6 Luna?

GPT-6 Luna is the better all-round choice, scoring 75/100 against Claude Fable 5.1 (61). It leads on price. Claude Fable 5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.

Which is cheaper, Claude Fable 5.1 or GPT-6 Luna?

GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). Claude Fable 5.1 costs $10.00 input / $50.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for GPT-6 Luna versus $20.00 for Claude Fable 5.1 (100× as much).

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): Claude Fable 5.1 87.0% and GPT-6 Luna 73.1%. On individual benchmarks: FrontierMath Tiers 1–3 — Claude Fable 5.1 90.2%, GPT-6 Luna 79.0%; OTIS Mock AIME 2024–2025 — Claude Fable 5.1 100%, GPT-6 Luna 98.9%; SimpleQA Verified — Claude Fable 5.1 70.8%, GPT-6 Luna 41.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Fable 5.1 and GPT-6 Luna yet, so there is no like-for-like coding score. On overall capability, Claude Fable 5.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GPT-6 Luna has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Fable 5.1. Maximum output per response: Claude Fable 5.1 up to 128,000, GPT-6 Luna up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Claude Fable 5.1 accepts text, images and PDFs; GPT-6 Luna accepts text, images and PDFs. They handle the same number of input types.

Are any of these open source?

No. Claude Fable 5.1 and GPT-6 Luna are proprietary and only available through APIs and apps.

Which is newer?

GPT-6 Luna is the newest, released Sep 22, 2026. Claude Fable 5.1 came out Sep 1, 2026. Knowledge cutoff: Claude Fable 5.1 Jun 2026, GPT-6 Luna May 18, 2026.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.

05 — Keep comparing

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