GLM 5.2 FP8
GLM-5.2 is Z.ai's flagship model for long-horizon coding and agentic work, released here as Z.ai's own FP8 checkpoint: 753B total parameters with 40B active per token, sparse attention with IndexShare, a solid 1M-token context, reasoning effort control, and an MIT license.
Model
GLM-5.2 is Z.ai's flagship model for long-horizon tasks, and the first in the GLM series to deliver that capability on a solid 1M-token context. It is a 78-layer Mixture-of-Experts model with 256 routed experts plus one shared expert and 8 experts active per token, for 40B active parameters out of 753B total. DeepSeek Sparse Attention with IndexShare shares one lightweight indexer across every four sparse-attention layers, reducing per-token FLOPs by 2.9x at 1M context, and an improved multi-token-prediction layer raises speculative-decoding acceptance length by up to 20%. Effort levels high and max let you trade capability against speed and cost on agentic coding work.
This is Z.ai's own FP8 quantization of GLM-5.2 (FP8 E4M3 with 128 by 128 block scaling and dynamic activation scaling), with the same architecture and 1M-token context as the BF16 model. The model is text-in, text-out, and the weights are released under the MIT license, which Z.ai describes as having no regional limits. Full details are in Z.ai's announcement and the model card.
Dedicated Endpoint
DocsA Dedicated Endpoint is your own deployment of GLM 5.2 FP8, on an inference stack that Modal tunes and autoscales. Bring fine-tuned weights if you have them. Compute is billed by the second, and only while it runs.
modal endpoint create --model zai-org/GLM-5.2-FP8