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GLM 4.6 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 4.6 and MiniMax M1.

Zhipu AI

GLM 4.6

Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...

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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...

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Technical Specifications

SpecificationGLM 4.6MiniMax M1
ProviderZhipu AIMiniMax
Context Window202,752 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 Date2025-09-302025-06-17

API Pricing Comparison

Input Price per Million Tokens

GLM 4.6

$0.43

MiniMax M1

$0.40

Output Price per Million Tokens

GLM 4.6

$1.74

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 4.6 Quirks & Gotchas

No developer gotchas reported.

MiniMax M1 Quirks & Gotchas

No developer gotchas reported.