GPT-5.6 Luna vs MiniMax M3.1 Flash
MiniMax M3.1 Flash leads the LLM Stats Score 48.5 to 44.1. MiniMax M3.1 Flash is 1.7x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
MiniMax M3.1 Flash leads the overall LLM Stats Score 48.5 to 44.1, ranking #29 overall.
In the 5 individual benchmarks reported for both models, MiniMax M3.1 Flash wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M3.1 Flash is roughly 1.7x 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
- you process long inputs — it offers a 1,050,000 token context window
Choose MiniMax M3.1 Flash
- overall performance matters — it scores 48.5 and ranks #29 on LLM Stats
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- cost matters — it's about 1.7x cheaper per token
- you want the most recent training data — it shipped Oct 2026
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 · 14 for MiniMax M3.1 Flash
GPT-5.6 Luna outperforms in 2 benchmarks (Agents' Last Exam, GDP.pdf), while MiniMax M3.1 Flash is better at 3 benchmarks (DeepSWE 1.1, OSWorld 2.0, Terminal-Bench 4.0).
MiniMax M3.1 Flash has a slight edge in benchmark performance.
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 1.3x more expensive than MiniMax M3.1 Flash ($0.15/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 2.0x more expensive than MiniMax M3.1 Flash ($0.60/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than MiniMax M3.1 Flash.*
* 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 M3.1 Flash's 1,000,000 tokens. MiniMax M3.1 Flash can generate longer responses up to 524,288 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 M3.1 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
MiniMax M3.1 Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while MiniMax M3.1 Flash was released on 2026-10-19.
MiniMax M3.1 Flash is 3 months newer than GPT-5.6 Luna.
Jul 9, 2026
3 months ago
Oct 19, 2026
0 days ago
3mo newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while MiniMax M3.1 Flash'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 M3.1 Flash's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. MiniMax M3.1 Flash is available from MiniMax.
GPT-5.6 Luna
MiniMax M3.1 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and MiniMax M3.1 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs MiniMax M3.1 Flash.