Text Gen · Model Guide · 5 min read

GLM-5.3

Z.ai's open flagship: 744B total parameters with 40B active — MIT-licensed frontier intelligence.

Basic Information

GLM-5.3 is the current flagship of Z.ai's GLM line: a mixture-of-experts model with roughly 744 billion total parameters and about 40 billion active per token. The GLM series is known for strong agentic and coding performance, and the 5.x generation added long-context and tooling improvements that make it a serious alternative to closed frontier APIs — with the notable bonus of MIT-licensed weights.

The 5.3 release (GLM-5.3-Flash shares the architecture at smaller scale) uses hybrid attention — only a fraction of layers keep the full KV-cache — which is why its long-context memory cost is dramatically lower than older designs of similar depth.

Best use cases

• Enterprise self-hosting where an MIT license simplifies legal review
• Agentic coding and tool-use pipelines (the GLM series is tuned for exactly this)
• Bilingual (Chinese/English) workloads — a traditional GLM strength
• High-throughput serving when the model fits your cluster

Computational Requirements

Cluster-class: hundreds of GB of VRAM are needed even at aggressive quantization, though the 40B active count keeps per-token cost reasonable once it is loaded.

• Realistic deployment is multi-node or cloud GPU rentals; the GLM-5.3-Flash sibling (321B) is the smaller open alternative.

Commercial license

MIT — one of the most permissive licenses in AI: commercial use, modification, redistribution, and closed products are all allowed with attribution. This is a major reason GLM weights show up in so many commercial stacks.