GLM 4.5 vs MiniMax M2.7
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GLM 4.5 and MiniMax M2.7.
GLM 4.5
GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...
MiniMax M2.7
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...
Technical Specifications
| Specification | GLM 4.5 | MiniMax M2.7 |
|---|---|---|
| Provider | Zhipu AI | MiniMax |
| Context Window | 131,072 tokens | 204,800 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-07-25 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
GLM 4.5
$0.60
MiniMax M2.7
$0.18
Output Price per Million Tokens
GLM 4.5
$2.20
MiniMax M2.7
$0.72
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
GLM 4.5 Quirks & Gotchas
No developer gotchas reported.
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.