Model Comparison
MiniMax M2.7 vs GLM-5.2Which is better in 2026?
GLM-5.2 significantly outperforms across most benchmarks. MiniMax M2.7 is 2.8x cheaper per token.
Verdict: MiniMax M2.7 vs GLM-5.2 — which is better?
MiniMax M2.7 (by MiniMax) and GLM-5.2 (by Zhipu AI) 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.
MiniMax M2.7 outperforms in 0 benchmarks, while GLM-5.2 is better at 3 benchmarks (NL2Repo, SWE-Bench Pro, Toolathlon). GLM-5.2 significantly outperforms across most benchmarks.
On price, MiniMax M2.7 is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.2 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M2.7 if…
- cost matters — it's about 2.8x cheaper per token
Choose GLM-5.2 if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jun 2026
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2.7 outperforms in 0 benchmarks, while GLM-5.2 is better at 3 benchmarks (NL2Repo, SWE-Bench Pro, Toolathlon).
GLM-5.2 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2.7 ($0.30/1M tokens) is 3.2x cheaper than GLM-5.2 ($0.95/1M tokens).
For output processing, MiniMax M2.7 ($1.20/1M tokens) is 2.5x cheaper than GLM-5.2 ($3.00/1M tokens).
In conclusion, GLM-5.2 is more expensive than MiniMax M2.7.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while GLM-5.2 is limited to 131,072 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
MiniMax M2.7 was released on 2026-03-18, while GLM-5.2 was released on 2026-06-16.
GLM-5.2 is 3 months newer than MiniMax M2.7.
Mar 18, 2026
4 months ago
Jun 16, 2026
1 months ago
3mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M2.7 is available from Fireworks, MiniMax, Novita. GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI.
MiniMax M2.7
GLM-5.2
Outputs Comparison
Key Takeaways
MiniMax M2.7
View detailsMiniMax
GLM-5.2
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M2.7 and GLM-5.2 side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about MiniMax M2.7 vs GLM-5.2.