MiniMax M3 vs Muse Glimmer-30B
MiniMax M3 leads the LLM Stats Score 41.9 to 35.5.
MiniMax · Meta · Updated for 2026
Which is better?
MiniMax M3 leads the overall LLM Stats Score 41.9 to 35.5, ranking #42 overall.
In the 7 individual benchmarks reported for both models, MiniMax M3 wins 6; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose MiniMax M3
- overall performance matters — it scores 41.9 and ranks #42 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 7 exact shared results
Choose Muse Glimmer-30B
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
35 reported for MiniMax M3 · 25 for Muse Glimmer-30B
MiniMax M3 outperforms in 6 benchmarks (MMMU-Pro, OmniDocBench 1.5, OSWorld-Verified, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.1), while Muse Glimmer-30B is better at 1 benchmark (MCP Atlas).
MiniMax M3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
MiniMax M3 has 398.4B more parameters than Muse Glimmer-30B, making it 1345.9% larger.
Context Window
Maximum input and output token capacity
Only MiniMax M3 specifies input context (512,000 tokens). Only MiniMax M3 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Both MiniMax M3 and Muse Glimmer-30B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
MiniMax M3
Muse Glimmer-30B
License
Usage and distribution terms
MiniMax M3 is licensed under MIT, while Muse Glimmer-30B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiniMax M3 was released on 2026-06-01, while Muse Glimmer-30B was released on 2026-08-10.
Muse Glimmer-30B is 2 months newer than MiniMax M3.
Jun 1, 2026
2 months ago
Aug 10, 2026
2 weeks ago
2mo newerKnowledge Cutoff
When training data ends
Muse Glimmer-30B has a documented knowledge cutoff of 2026-01-04, while MiniMax M3's cutoff date is not specified.
We can confirm Muse Glimmer-30B's training data extends to 2026-01-04, but cannot make a direct comparison without MiniMax M3's cutoff date.
—
Jan 2026
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M3 and Muse Glimmer-30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M3 vs Muse Glimmer-30B.