GLM-4-Air
GLM-4-Air has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating long context
- Workloads that can use a 128k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- GLM-4
- Released
- 2024-06-05
- Context
- 128k
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
GLM-4-Air is a cost-effective large language model (LLM) developed by Zhipu AI and Tsinghua University, designed as a more affordable and faster alternative to the full GLM-4 model while maintaining comparable performance. It builds on the Generalized Language Model (GLM) framework, excelling in tasks involving general language understanding, instruction following, and long-context processing. Trained on a massive dataset spanning multiple languages, GLM-4-Air utilizes efficient techniques like FlashAttention and offers notable features such as lower inference costs and faster speeds, making it an accessible option for a wide range of applications. The model's open-source nature further enhances its availability for users.
GLM-4-Air is a model in the GLM-4 family. The structured metadata tracks a 128k-token context window. No headline benchmark score is tracked for GLM-4-Air yet.
Top use-case fit
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Long context
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.