Hyperbolic vs Z.AI: Token Pricing, Speed & Intelligence
Full comparison of Hyperbolic and Z.AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Hyperbolic
Open-source inference marketplace — Llama, DeepSeek R1, and more
Hyperbolic provides a marketplace for open-source model inference, hosting Llama 3.3, DeepSeek R1, and other popular models at competitive prices. Their platform emphasises accessibility and affordability, making frontier open-weight models available to developers and researchers at low cost.
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
Hyperbolic
Z.AI
Key differentiators
One of the most affordable inference marketplaces for open-weight models — ideal for researchers and cost-sensitive workloads.
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
Hyperbolic FAQs
What models does Hyperbolic offer?
Hyperbolic hosts Llama 3.3 70B, DeepSeek R1, and other popular open-weight models. Their marketplace approach means the catalog evolves frequently.
How does Hyperbolic pricing compare to competitors?
Hyperbolic is among the most affordable options for open-weight model inference, often undercutting Together AI and Fireworks AI on price. This makes it attractive for high-volume or cost-sensitive workloads.
Is Hyperbolic reliable for production use?
Hyperbolic is newer and less established than providers like Together AI or Fireworks AI. It's well-suited for research, prototyping, and cost-sensitive workloads, but for mission-critical production use, a more established provider may be preferable.
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
Hyperbolic — Open-source inference marketplace — Llama, DeepSeek R1, and more
Hyperbolic provides a marketplace for open-source model inference, hosting Llama 3.3, DeepSeek R1, and other popular models at competitive prices. Their platform emphasises accessibility and affordability, making frontier open-weight models available to developers and researchers at low cost.
One of the most affordable inference marketplaces for open-weight models — ideal for researchers and cost-sensitive workloads.
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
Hyperbolic
- ▸Among the lowest prices for open-weight model inference
- ▸DeepSeek R1 and Llama 3.3 available at competitive rates
- ▸Marketplace model — broad model selection
Z.AI
- ▸1M token context window
- ▸Strong Chinese and English bilingual performance
- ▸Enterprise-grade reliability
Provider category context
Hyperbolic is a inference api, founded in 2023. Z.AI is a frontier lab, founded in 2019. Hyperbolic 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 Hyperbolic if you need among the lowest prices for open-weight model inference. 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.