GLM 4.5V vs MiniMax M3
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 4.5V and MiniMax M3.
GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...
MiniMax M3
MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...
Technical Specifications
| Specification | GLM 4.5V | MiniMax M3 |
|---|---|---|
| Provider | Zhipu AI | MiniMax |
| Context Window | 65,536 tokens | 1,048,576 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 | beta |
| API Available | Yes | Yes |
| Released Date | 2025-08-11 | 2026-05-31 |
API Pricing Comparison
Input Price per Million Tokens
GLM 4.5V
$0.60
MiniMax M3
$0.30
Output Price per Million Tokens
GLM 4.5V
$1.80
MiniMax M3
$1.20
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 4.5V Quirks & Gotchas
No developer gotchas reported.
MiniMax M3 Quirks & Gotchas
No developer gotchas reported.