Model Comparison
GLM-5 vs MiniMax M2
GLM-5 significantly outperforms across most benchmarks. MiniMax M2 is 3.0x cheaper per token.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while MiniMax M2 is better at 0 benchmarks.
GLM-5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 3.3x more expensive than MiniMax M2 ($0.30/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 2.7x more expensive than MiniMax M2 ($1.20/1M tokens).
In conclusion, GLM-5 is more expensive than MiniMax M2.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5 has 514.0B more parameters than MiniMax M2, making it 223.5% larger.
Context Window
Maximum input and output token capacity
MiniMax M2 accepts 1,000,000 input tokens compared to GLM-5's 200,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while GLM-5 is limited to 128,000 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while MiniMax M2 was released on 2025-10-27.
GLM-5 is 4 months newer than MiniMax M2.
Feb 11, 2026
3 months ago
3mo newerOct 27, 2025
6 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5 is available from FriendliAI, ZAI. MiniMax M2 is available from MiniMax, Novita.
GLM-5
MiniMax M2
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
MiniMax M2
View detailsMiniMax
Detailed Comparison
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FAQ
Common questions about GLM-5 vs MiniMax M2.