ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GPT-6 Luna vs MiniMax-M3

GPT-6 Luna comes out ahead, 86 to 73 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT-6 Luna

    Released Sep 22, 2026

    86/100
    • ECI—
    • Price$0.10 / $0.50
    • Context1.05M
    Full specs Remove GPT-6 Luna

  2. MiniMax

    MiniMax-M3

    Released Jun 1, 2026

    73/100
    • ECI147.0
    • Price$0.30 / $1.20
    • Context1.05M
    Full specs Remove MiniMax-M3

  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 86/100 against MiniMax-M3 (73). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GPT-6 Luna has no Capabilities Index score yet.

  • CapabilityGPT-6 LunaShared benchmarks: GPT-6 Luna 94.7% · MiniMax-M3 81.0%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · MiniMax-M3 $0.525 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameGPT-6 Luna 1,050,000 · MiniMax-M3 1,048,576 tokens
  • Widest inputsSame inputsGPT-6 Luna: Text, Images, PDFs · MiniMax-M3: Text, Images, Video
  • Self-hostingMiniMax-M3Publishes downloadable weights
How the score is built
MeasureWeightGPT-6 LunaMiniMax-M3
CapabilityShared benchmarks50%9581
Price25%8363
Inputs & features15%8070
Context window10%6161
Overall100%86/10073/100
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 MiniMax-M3 specifications side by side
SpecificationGPT-6 LunaOpenAIMiniMax-M3MiniMax
Capability
Capabilities Index (ECI)—147.0
ECI rank—#62 of 148
GPQA DiamondGraduate-level science questions90.5%90.9% (best)
FrontierMath Tiers 1–3Research-level mathematics79.0%—
OTIS Mock AIME 2024–2025Competition mathematics98.9% (best)71.1%
SimpleQA VerifiedShort factual questions41.4%—
Price per million tokens
Input$0.10 (best)$0.30
Output$0.50 (best)$1.20
Cached input$0.01 (best)$0.06
Blended (3:1)$0.20 (best)$0.525
Long-context rateOver 272K: $0.20 / $0.75Over 512K: $0.60 / $2.40
Price sourceOfficial OpenAI APIOfficial MiniMax (minimax.io) API
Limits
Context window1,050,000 tokens (best)1,048,576 tokens
Max output128,000 tokens512,000 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesNo
AudioNoNo
VideoNoYes
ReasoningYeslow · medium · high · xhigh · maxYes
Tool callingYesYes
Structured outputYesNo
Availability
WeightsProprietaryOpen
API model IDgpt-6-lunaMiniMax-M3
API providers2442 (best)
ReleasedSep 22, 2026Jun 1, 2026
Knowledge cutoffMay 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 Luna$2.00
  • MiniMax-M3$5.40
04 — Questions

Which should you choose?

Which is better: GPT-6 Luna or MiniMax-M3?

GPT-6 Luna is the better all-round choice, scoring 86/100 against MiniMax-M3 (73). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GPT-6 Luna has no Capabilities Index score yet.

Which is cheaper, GPT-6 Luna or MiniMax-M3?

GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). MiniMax-M3 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) 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 $0.525 for MiniMax-M3 (2.6× 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 and OTIS Mock AIME 2024–2025): GPT-6 Luna 94.7% and MiniMax-M3 81.0%. On individual benchmarks: GPQA Diamond — MiniMax-M3 90.9%, GPT-6 Luna 90.5%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, MiniMax-M3 71.1%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-6 Luna and MiniMax-M3 yet, so there is no like-for-like coding score. On overall capability, GPT-6 Luna 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?

Their context windows are effectively the same size: GPT-6 Luna 1,050,000 and MiniMax-M3 1,048,576 tokens. Maximum output per response: GPT-6 Luna up to 128,000, MiniMax-M3 up to 512,000 tokens.

Which can read images, PDFs, audio or video?

GPT-6 Luna accepts text, images and PDFs; MiniMax-M3 accepts text, images and video. They handle the same number of input types.

Are any of these open source?

MiniMax-M3 publishes its weights and can be self-hosted; GPT-6 Luna is proprietary.

Which is newer?

GPT-6 Luna is the newest, released Sep 22, 2026. MiniMax-M3 came out Jun 1, 2026. Knowledge cutoff: 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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