Deep Infra vs Z.AI: Token Pricing, Speed & Intelligence
Full comparison of Deep Infra and Z.AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Deep Infra
The cheapest inference API for open-weight models — Llama, Mistral, and more
Deep Infra is an inference-focused API provider specialising in open-weight models at extremely competitive prices. Consistently among the cheapest providers for Llama 3, Mistral, and DeepSeek models, making it the go-to choice for cost-sensitive production inference.
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.
Key metrics
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Live token pricing
Strengths & weaknesses
Deep Infra
Z.AI
Key differentiators
The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.
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
Deep Infra FAQs
How cheap is Deep Infra compared to other providers?
Deep Infra is consistently among the cheapest providers for open-weight models. For example, Llama 3.1 8B is available at $0.02–0.05/1M tokens, and Llama 3.3 70B at around $0.10/1M tokens — often 30–50% below comparable providers.
What models does Deep Infra support?
Deep Infra hosts a wide range of open-weight models including the full Llama 3.x family, Mistral, Mixtral, DeepSeek V3 and R1, Qwen, and many others. The catalog is updated frequently as new models are released.
Is Deep Infra OpenAI-compatible?
Yes. Deep Infra provides an OpenAI-compatible API, so you can use the OpenAI SDK by pointing it at the Deep Infra endpoint. This makes migration straightforward.
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
Deep Infra — The cheapest inference API for open-weight models — Llama, Mistral, and more
Deep Infra is an inference-focused API provider specialising in open-weight models at extremely competitive prices. Consistently among the cheapest providers for Llama 3, Mistral, and DeepSeek models, making it the go-to choice for cost-sensitive production inference.
The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.
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.
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
Deep Infra
- ▸Consistently lowest prices for open-weight models
- ▸Wide model catalog including Llama, Mistral, DeepSeek
- ▸OpenAI-compatible API
Z.AI
- ▸1M token context window
- ▸Strong Chinese and English bilingual performance
- ▸Enterprise-grade reliability
Provider category context
Deep Infra is a inference api, founded in 2023. Z.AI is a frontier lab, founded in 2019. Deep Infra as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. Z.AI as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Deep Infra if you need consistently lowest prices for open-weight models. Choose Z.AI if you need 1m token context window. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.