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

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

Mistral

European frontier AI — Mistral Large, Codestral, and open models

Mistral AI is a Paris-based lab that trains both proprietary and open-weight models. Mistral Large competes with GPT-4 class models at lower prices, while Codestral is purpose-built for code generation with a 262K context window. Several Mistral models are open-weight and available for self-hosting.

CodingEuropean complianceOpen-sourceCost-efficiencyChat
Proprietary modelsHosts open weights

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

Mistral

Several open-weight models available for self-hosting
Codestral purpose-built for code with 262K context
European data sovereignty — GDPR-native
Competitive pricing vs. GPT-4 class models
Mistral Small is one of the cheapest capable models at $0.10/1M
Intelligence scores trail OpenAI and Anthropic at frontier tier
Smaller ecosystem than OpenAI
No vision support on smaller models

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

Mistral

The only frontier lab offering open-weight models alongside proprietary ones — giving teams the flexibility to self-host or use the API.

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

Mistral FAQs

How much does the Mistral API cost?

Mistral Large costs $2.00/1M input and $6.00/1M output tokens. Mistral Small is $0.10/$0.30 per 1M tokens — one of the cheapest capable models available. Codestral for code generation is priced separately.

Are Mistral models open-weight?

Some are. Mistral 7B, Mixtral 8x7B, and Mixtral 8x22B are open-weight and available on Hugging Face for self-hosting. Mistral Large and Codestral are proprietary and only available via the API.

What is Codestral?

Codestral is Mistral's code-specialised model with a 262K context window. It supports 80+ programming languages and is optimised for code completion, generation, and explanation tasks.

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

MistralEuropean frontier AI — Mistral Large, Codestral, and open models

Mistral AI is a Paris-based lab that trains both proprietary and open-weight models. Mistral Large competes with GPT-4 class models at lower prices, while Codestral is purpose-built for code generation with a 262K context window. Several Mistral models are open-weight and available for self-hosting.

The only frontier lab offering open-weight models alongside proprietary ones — giving teams the flexibility to self-host or use the API.

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

Mistral

  • Several open-weight models available for self-hosting
  • Codestral purpose-built for code with 262K context
  • European data sovereignty — GDPR-native

Z.AI

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

Provider category context

Mistral is a frontier lab, founded in 2023. 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 Mistral and Z.AI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Mistral leads on several open-weight models available for self-hosting, 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.