Fireworks AI vs Z.AI: Token Pricing, Speed & Intelligence
Full comparison of Fireworks AI and Z.AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Fireworks AI
Production-grade open-source inference with fast cold starts
Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. They host Llama, DeepSeek R1, and other popular open-source models with competitive per-token pricing and a serverless deployment model that minimises cold-start times.
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.
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Live token pricing
Strengths & weaknesses
Fireworks AI
Z.AI
Key differentiators
Production-grade reliability with 320+ tokens/sec throughput and DeepSeek R1 reasoning at $3/1M input — a strong balance of speed and capability.
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
Fireworks AI FAQs
What models does Fireworks AI offer?
Fireworks AI hosts Llama 3.3 70B, DeepSeek R1, Mixtral, and other popular open-weight models. They focus on production-ready models with optimised inference rather than the broadest possible catalog.
How much does Fireworks AI cost?
Llama 3.3 70B costs $0.90/1M tokens (input and output). DeepSeek R1 is $3.00/1M input and $8.00/1M output. Pricing is competitive with other inference API providers.
How does Fireworks AI compare to Together AI?
Fireworks AI offers faster throughput (320 vs 190 tokens/sec on Llama 3.3 70B) and stronger production reliability. Together AI has a larger model catalog and fine-tuning support. Choose Fireworks for production speed, Together for model variety.
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
Fireworks AI — Production-grade open-source inference with fast cold starts
Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. They host Llama, DeepSeek R1, and other popular open-source models with competitive per-token pricing and a serverless deployment model that minimises cold-start times.
Production-grade reliability with 320+ tokens/sec throughput and DeepSeek R1 reasoning at $3/1M input — a strong balance of speed and capability.
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
Fireworks AI
- ▸320+ tokens/sec on Llama 3.3 70B — fast GPU inference
- ▸DeepSeek R1 hosting with strong reasoning capability
- ▸Production-grade reliability with SLAs
Z.AI
- ▸1M token context window
- ▸Strong Chinese and English bilingual performance
- ▸Enterprise-grade reliability
Provider category context
Fireworks AI is a inference api, founded in 2022. Z.AI is a frontier lab, founded in 2019. Fireworks AI 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 Fireworks AI if you need 320+ tokens/sec on llama 3.3 70b — fast gpu 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.