GPT-6 Luna vs MiniMax M2.7
GPT-6 Luna leads the LLM Stats Score 43.1 to 35.4. GPT-6 Luna is 2.6x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 43.1 to 35.4, ranking #55 overall.
On price, GPT-6 Luna is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Luna
- overall performance matters — it scores 43.1 and ranks #55 on LLM Stats
- your work emphasizes agents — it leads those capability indexes
- cost matters — it's about 2.6x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose MiniMax M2.7
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GPT-6 Luna · 11 for MiniMax M2.7
GPT-6 Luna and MiniMax M2.7don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Luna ($0.10/1M tokens) is 3.0x cheaper than MiniMax M2.7 ($0.30/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.4x cheaper than MiniMax M2.7 ($1.20/1M tokens).
In conclusion, MiniMax M2.7 is more expensive than GPT-6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Luna accepts 1,050,000 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas MiniMax M2.7 does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Luna
MiniMax M2.7
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while MiniMax M2.7 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-6 Luna was released on 2026-09-22, while MiniMax M2.7 was released on 2026-03-18.
GPT-6 Luna is 6 months newer than MiniMax M2.7.
Sep 22, 2026
4 weeks ago
6mo newerMar 18, 2026
7 months ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while MiniMax M2.7's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without MiniMax M2.7's cutoff date.
May 2026
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Provider Availability
GPT-6 Luna is available from OpenAI. MiniMax M2.7 is available from Fireworks, MiniMax, Novita, DeepInfra.
GPT-6 Luna
MiniMax M2.7
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and MiniMax M2.7 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs MiniMax M2.7.