ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GPT-6.1 Sol vs GPT-6 Luna

GPT-6 Luna comes out ahead, 78 to 69 on our weighted score, and it is the cheaper option too.

  1. OpenAI

    GPT-6.1 Sol

    Released Sep 29, 2026

    69/100
    • ECI—
    • Price$2.00 / $10.00
    • Context1.05M
    Full specs Remove GPT-6.1 Sol
  2. 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

  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 GPT-6.1 Sol (69). It leads on price. GPT-6.1 Sol 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-6.1 Sol and GPT-6 Luna has no Capabilities Index score yet.

  • CapabilityGPT-6.1 SolShared benchmarks: GPT-6.1 Sol 90.7% · GPT-6 Luna 77.4%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · GPT-6.1 Sol $4.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameGPT-6.1 Sol 1,050,000 · GPT-6 Luna 1,050,000 tokens
  • Widest inputsSame inputsGPT-6.1 Sol: Text, Images, PDFs · GPT-6 Luna: Text, Images, PDFs
  • Self-hostingNo open weightsBoth are available only through APIs
How the score is built
MeasureWeightGPT-6.1 SolGPT-6 Luna
CapabilityShared benchmarks50%9177
Price25%2183
Inputs & features15%8080
Context window10%6161
Overall100%69/10078/100
02 — Side by side

Every spec in one table

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

GPT-6.1 Sol vs GPT-6 Luna specifications side by side
SpecificationGPT-6.1 SolOpenAIGPT-6 LunaOpenAI
Capability
Capabilities Index (ECI)——
ECI rank——
GPQA DiamondGraduate-level science questions95.4% (best)90.5%
FrontierMath Tiers 1–3Research-level mathematics93.7% (best)79.0%
OTIS Mock AIME 2024–2025Competition mathematics100% (best)98.9%
SimpleQA VerifiedShort factual questions73.9% (best)41.4%
Price per million tokens
Input$2.00$0.10 (best)
Output$10.00$0.50 (best)
Cached input$0.10$0.01 (best)
Blended (3:1)$4.00$0.20 (best)
Long-context rateOver 272K: $4.00 / $15.00Over 272K: $0.20 / $0.75
Price sourceOfficial OpenAI APIOfficial OpenAI API
Limits
Context window1,050,000 tokens1,050,000 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-6.1-solgpt-6-luna
API providers2124 (best)
ReleasedSep 29, 2026Sep 22, 2026
Knowledge cutoffApr 30, 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.

  • GPT-6.1 Sol$40.00
  • GPT-6 Luna$2.00
04 — Questions

Which should you choose?

Which is better: GPT-6.1 Sol or GPT-6 Luna?

GPT-6 Luna is the better all-round choice, scoring 78/100 against GPT-6.1 Sol (69). It leads on price. GPT-6.1 Sol 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-6.1 Sol and GPT-6 Luna has no Capabilities Index score yet.

Which is cheaper, GPT-6.1 Sol or GPT-6 Luna?

GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). GPT-6.1 Sol costs $2.00 input / $10.00 output per million tokens (official OpenAI 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 GPT-6.1 Sol (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): GPT-6.1 Sol 90.7% and GPT-6 Luna 77.4%. On individual benchmarks: GPQA Diamond — GPT-6.1 Sol 95.4%, GPT-6 Luna 90.5%; FrontierMath Tiers 1–3 — GPT-6.1 Sol 93.7%, GPT-6 Luna 79.0%; OTIS Mock AIME 2024–2025 — GPT-6.1 Sol 100%, GPT-6 Luna 98.9%; SimpleQA Verified — GPT-6.1 Sol 73.9%, GPT-6 Luna 41.4%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-6.1 Sol and GPT-6 Luna yet, so there is no like-for-like coding score. On overall capability, GPT-6.1 Sol 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-6.1 Sol and GPT-6 Luna share the same 1,050,000-token context window. Maximum output per response: GPT-6.1 Sol up to 128,000, GPT-6 Luna up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GPT-6.1 Sol 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. GPT-6.1 Sol and GPT-6 Luna are proprietary and only available through APIs and apps.

Which is newer?

GPT-6.1 Sol is the newest, released Sep 29, 2026. GPT-6 Luna came out Sep 22, 2026. Knowledge cutoff: GPT-6.1 Sol Apr 30, 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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