โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

GLM 4.5V vs MiniMax M1

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 M1.

Zhipu AI

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,...

View Full Specs
MiniMax

MiniMax M1

MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...

View Full Specs

Technical Specifications

SpecificationGLM 4.5VMiniMax M1
ProviderZhipu AIMiniMax
Context Window65,536 tokens1,000,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2025-08-112025-06-17

API Pricing Comparison

Input Price per Million Tokens

GLM 4.5V

$0.60

MiniMax M1

$0.40

Output Price per Million Tokens

GLM 4.5V

$1.80

MiniMax M1

$2.20

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 M1 Quirks & Gotchas

No developer gotchas reported.