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MiniMax vs Z.AI: Token Pricing, Speed & Intelligence

Full comparison of MiniMax and Z.AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.

MiniMax

Long-context frontier models with 1M token windows

MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.

ChatLong-document analysisAgentic workflowsEnterprise AI
Proprietary models

Z.AI

GLM frontier models with 1M context

Z.AI (formerly Zhipu AI) develops the GLM series of large language models. GLM-5.2 supports a 1M token context window and is designed for enterprise-grade chat, coding, and long-document tasks.

ChatCodingLong-document analysisEnterprise AI
Proprietary models

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

MiniMax

1M token context window
Competitive pricing
Strong multilingual performance
Smaller international developer community
Less third-party tooling than OpenAI

Z.AI

1M token context window
Strong Chinese and English bilingual performance
Enterprise-grade reliability
Smaller international developer community
Fewer third-party integrations than OpenAI

Key differentiators

MiniMax

MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.

Z.AI

GLM-5.2 offers a 1M token context window at $1.11/1M input tokens, making it one of the most cost-effective long-context models available.

Frequently asked questions

MiniMax FAQs

What is MiniMax M2.7?

MiniMax M2.7 is MiniMax's latest chat model, supporting a 205K token context window. It is designed for enterprise chat, long-document analysis, and agentic tasks.

Is MiniMax available internationally?

Yes. The MiniMax API is accessible globally, and models are also available through OpenRouter and other inference aggregators.

Z.AI FAQs

What is GLM-5.2?

GLM-5.2 is the latest model in Zhipu AI's GLM series, supporting a 1M token context window. It is designed for long-document analysis, coding, and enterprise chat applications.

How does Z.AI compare to other Chinese LLM providers?

Z.AI's GLM models compete with Alibaba's Qwen and Baidu's ERNIE series. GLM-5.2 stands out for its 1M context window and competitive pricing.

Provider resources

MiniMaxLong-context frontier models with 1M token windows

MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.

MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.

Z.AIGLM frontier models with 1M context

Z.AI (formerly Zhipu AI) develops the GLM series of large language models. GLM-5.2 supports a 1M token context window and is designed for enterprise-grade chat, coding, and long-document tasks.

GLM-5.2 offers a 1M token context window at $1.11/1M input tokens, making it one of the most cost-effective long-context models available.

Key strengths compared

MiniMax

  • 1M token context window
  • Competitive pricing
  • Strong multilingual performance

Z.AI

  • 1M token context window
  • Strong Chinese and English bilingual performance
  • Enterprise-grade reliability

Provider category context

MiniMax is a frontier lab, founded in 2021. Z.AI is a frontier lab, founded in 2019. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both MiniMax and Z.AI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: MiniMax leads on 1m token context window, while Z.AI leads on 1m token context window. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.