GPT-5.6 Luna vs MiniMax M3
GPT-5.6 Luna and MiniMax M3 are closely matched at 45.4 and 41.4 on the LLM Stats Score. GPT-5.6 Luna is 1.2x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
GPT-5.6 Luna and MiniMax M3 are closely matched on the overall LLM Stats Score at 45.4 and 41.4.
In the 5 individual benchmarks reported for both models, GPT-5.6 Luna wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5.6 Luna is roughly 1.2x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.6 Luna
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
- cost matters — it's about 1.2x 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 Jul 2026
Choose MiniMax M3
- 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
45 reported for GPT-5.6 Luna · 35 for MiniMax M3
GPT-5.6 Luna outperforms in 4 benchmarks (FrontierCode 1.1, MMMU-Pro, SWE-Bench Pro, Terminal-Bench 2.1), while MiniMax M3 is better at 1 benchmark (BrowseComp).
GPT-5.6 Luna significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($0.20/1M tokens) is 1.5x cheaper than MiniMax M3 ($0.30/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) costs the same as MiniMax M3 ($1.20/1M tokens).
In conclusion, MiniMax M3 is more expensive than GPT-5.6 Luna.*
* 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 M3's 512,000 tokens. MiniMax M3 can generate longer responses up to 131,072 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.6 Luna and MiniMax M3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
MiniMax M3
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while MiniMax M3 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 M3 was released on 2026-06-01.
GPT-5.6 Luna is 1 month newer than MiniMax M3.
Jul 9, 2026
1 months ago
1mo newerJun 1, 2026
3 months ago
Knowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while MiniMax M3'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 M3's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. MiniMax M3 is available from Fireworks, MiniMax, Novita, Together.
GPT-5.6 Luna
MiniMax M3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and MiniMax M3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs MiniMax M3.