Model Comparison
GPT-5.6 Luna vs MiniMax M2Which is better in 2026?
GPT-5.6 Luna significantly outperforms across most benchmarks. MiniMax M2 is 4.3x cheaper per token.
Verdict: GPT-5.6 Luna vs MiniMax M2 — which is better?
GPT-5.6 Luna (by OpenAI) and MiniMax M2 (by MiniMax) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT-5.6 Luna outperforms in 2 benchmarks (BrowseComp, GPQA), while MiniMax M2 is better at 0 benchmarks. GPT-5.6 Luna significantly outperforms across most benchmarks.
On price, MiniMax M2 is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-5.6 Luna if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Jul 2026
Choose MiniMax M2 if…
- cost matters — it's about 4.3x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5.6 Luna outperforms in 2 benchmarks (BrowseComp, GPQA), while MiniMax M2 is better at 0 benchmarks.
GPT-5.6 Luna significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($1.00/1M tokens) is 3.3x more expensive than MiniMax M2 ($0.30/1M tokens).
For output processing, GPT-5.6 Luna ($6.00/1M tokens) is 5.0x more expensive than MiniMax M2 ($1.20/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than MiniMax M2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Luna accepts 1,050,000 input tokens compared to MiniMax M2's 1,000,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
GPT-5.6 Luna supports multimodal inputs, whereas MiniMax M2 does not.
GPT-5.6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.6 Luna
MiniMax M2
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while MiniMax M2 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-5.6 Luna was released on 2026-07-09, while MiniMax M2 was released on 2025-10-27.
GPT-5.6 Luna is 9 months newer than MiniMax M2.
Jul 9, 2026
2 weeks ago
8mo newerOct 27, 2025
9 months ago
Knowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while MiniMax M2's cutoff date is not specified.
We can confirm GPT-5.6 Luna's training data extends to 2026-02-16, but cannot make a direct comparison without MiniMax M2's cutoff date.
Feb 2026
—
Provider Availability
GPT-5.6 Luna is available from OpenAI. MiniMax M2 is available from MiniMax, Novita.
GPT-5.6 Luna
MiniMax M2
Outputs Comparison
Key Takeaways
GPT-5.6 Luna
View detailsOpenAI
MiniMax M2
View detailsMiniMax
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and MiniMax M2 side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about GPT-5.6 Luna vs MiniMax M2.