ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GPT-6 Luna vs Claude Sonnet 5.5

GPT-6 Luna comes out ahead, 78 to 65 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT-6 Luna

    Released Sep 22, 2026

    78/100
    • ECI—
    • Price$0.10 / $0.50
    • Context1.05M
    Full specs Remove GPT-6 Luna

  2. Anthropic

    Claude Sonnet 5.5

    Released Sep 28, 2026

    65/100
    • ECI165.2
    • Price$2.00 / $10.00
    • Context1M
    Full specs Remove Claude Sonnet 5.5

  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 78/100 against Claude Sonnet 5.5 (65). It leads on price. Claude Sonnet 5.5 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.

  • CapabilityClaude Sonnet 5.5Shared benchmarks: Claude Sonnet 5.5 82.7% · GPT-6 Luna 77.4%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · Claude Sonnet 5.5 1,000,000 tokens
  • Widest inputsSame inputsGPT-6 Luna: Text, Images, PDFs · Claude Sonnet 5.5: Text, Images, PDFs
  • Self-hostingNo open weightsBoth are available only through APIs
How the score is built
MeasureWeightGPT-6 LunaClaude Sonnet 5.5
CapabilityShared benchmarks50%7783
Price25%8321
Inputs & features15%8080
Context window10%6160
Overall100%78/10065/100
02 — Side by side

Every spec in one table

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

GPT-6 Luna vs Claude Sonnet 5.5 specifications side by side
SpecificationGPT-6 LunaOpenAIClaude Sonnet 5.5Anthropic
Capability
Capabilities Index (ECI)—165.2
ECI rank—#3 of 148
GPQA DiamondGraduate-level science questions90.5%95.6% (best)
FrontierMath Tiers 1–3Research-level mathematics79.0%88.8% (best)
OTIS Mock AIME 2024–2025Competition mathematics98.9%100% (best)
SimpleQA VerifiedShort factual questions41.4%46.5% (best)
Price per million tokens
Input$0.10 (best)$2.00
Output$0.50 (best)$10.00
Cached input$0.01 (best)$0.20
Blended (3:1)$0.20 (best)$4.00
Long-context rateOver 272K: $0.20 / $0.75Same rate
Price sourceOfficial OpenAI APIOfficial Anthropic API
Limits
Context window1,050,000 tokens (best)1,000,000 tokens
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 IDgpt-6-lunaclaude-sonnet-5-5
API providers24 (best)23
ReleasedSep 22, 2026Sep 28, 2026
Knowledge cutoffMay 18, 2026Jun 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.

  • GPT-6 Luna$2.00
  • Claude Sonnet 5.5$40.00
04 — Questions

Which should you choose?

Which is better: GPT-6 Luna or Claude Sonnet 5.5?

GPT-6 Luna is the better all-round choice, scoring 78/100 against Claude Sonnet 5.5 (65). It leads on price. Claude Sonnet 5.5 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, 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, GPT-6 Luna or Claude Sonnet 5.5?

GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). Claude Sonnet 5.5 costs $2.00 input / $10.00 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 $4.00 for Claude Sonnet 5.5 (20× as much).

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): Claude Sonnet 5.5 82.7% and GPT-6 Luna 77.4%. On individual benchmarks: GPQA Diamond — Claude Sonnet 5.5 95.6%, GPT-6 Luna 90.5%; FrontierMath Tiers 1–3 — Claude Sonnet 5.5 88.8%, GPT-6 Luna 79.0%; OTIS Mock AIME 2024–2025 — Claude Sonnet 5.5 100%, GPT-6 Luna 98.9%; SimpleQA Verified — Claude Sonnet 5.5 46.5%, GPT-6 Luna 41.4%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-6 Luna and Claude Sonnet 5.5 yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 5.5 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 Sonnet 5.5. Maximum output per response: GPT-6 Luna up to 128,000, Claude Sonnet 5.5 up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GPT-6 Luna accepts text, images and PDFs; Claude Sonnet 5.5 accepts text, images and PDFs. They handle the same number of input types.

Are any of these open source?

No. GPT-6 Luna and Claude Sonnet 5.5 are proprietary and only available through APIs and apps.

Which is newer?

Claude Sonnet 5.5 is the newest, released Sep 28, 2026. GPT-6 Luna came out Sep 22, 2026. Knowledge cutoff: GPT-6 Luna May 18, 2026, Claude Sonnet 5.5 Jun 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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