FP8 Dynamically quantized GLM-4.7-Flash
FP8 Dynamically quantized by Unsloth for fast and premium inference.
You can read our vLLM deployment guide.
GLM-4.7-Flash
👋 Join our Discord community.
📖 Check out the GLM-4.7 technical blog, technical report(GLM-4.5).
📍 Use GLM-4.7-Flash API services on Z.ai API Platform.
👉 One click to GLM-4.7.
Introduction
GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.
Performances on Benchmarks
Serve GLM-4.7-Flash Locally
For local deployment, GLM-4.7-Flash supports inference frameworks including vLLM and SGLang. Comprehensive deployment
instructions are available in the official Github repository.
vLLM and SGLang only support GLM-4.7-Flash on their main branches.
vLLM
- using pip (must use pypi.org as the index url):
SGLang
- using pip install sglang from source, then update transformers to the latest main branch.
transformers
using with transformers as
and then run:
vLLM
SGLang
Citation
If you find our work useful in your research, please consider citing the following paper: