Quick Overview of Qwen 3.8 Flash Next and GLM 5.3 Flash Open-Weight Models

Two large open-weight models were released this week: Qwen 3.8 Flash Next and GLM 5.3 Flash. This quick summary covers their architectures, quantization and hardware requirements, and the current state of llama.cpp support, ahead of a dedicated follow-up video.

■ Qwen 3.8 Flash Next
- 125B parameters in total: 6B active plus a separate 51B n-gram table
- 2-bit quantization fits 128GB; running on 64GB depends on keeping the n-gram table on disk
- llama.cpp support was merged only days ago and is still being optimized

■ GLM 5.3 Flash
- MoE model with 321B total parameters, using 18B per token
- 2-bit quantization runs on 128GB desktops, with a 3-bit option to allocate less space to context
- llama.cpp support was still in progress at the time of recording

■ Upcoming content
- A detailed video comparing both models against DeepSeek v4 flash and 1.3.8 27b

If you run language models locally, this summary lets you quickly check hardware requirements and software readiness for these releases. Use it as a reference before the full performance and quality comparison is published.