GLM-4

GLM-4 is Zhipu AI’s fourth-generation General Language Model, featuring strong multilingual capabilities and tool-use support.


Task	Text Generation
Architecture	`GlmForCausalLM` / `Glm4ForCausalLM`
Parameters	9B – 32B
HF Org	zai-org

Available Models

GLM-4-9B-Chat-HF (GlmForCausalLM): 9B
GLM-4-32B-0414 (Glm4ForCausalLM): 32B

Architectures

GlmForCausalLM — GLM-4 series
Glm4ForCausalLM — GLM-4-0414 series

Example HF Models

Model	HF ID
GLM-4-9B-Chat-HF	`zai-org/glm-4-9b-chat-hf`
GLM-4-32B-0414	`zai-org/GLM-4-32B-0414`

Example Recipes

Recipe	Description
glm_4_9b_chat_hf_squad.yaml	SFT — GLM-4 9B on SQuAD
glm_4_9b_chat_hf_hellaswag_fp8.yaml	SFT — GLM-4 9B on HellaSwag with FP8

Try with NeMo AutoModel

1. Install (full instructions):

$ pip install nemo-automodel

2. Clone the repo to get the example recipes:

$ git clone https://github.com/NVIDIA-NeMo/Automodel.git
$ cd Automodel

3. Run the recipe from inside the repo:

$ automodel --nproc-per-node=8 examples/llm_finetune/glm/glm_4_9b_chat_hf_squad.yaml

Run with Docker

1. Pull the container and mount a checkpoint directory:

$ docker run --gpus all -it --rm \
>   --shm-size=8g \
>   -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
>   nvcr.io/nvidia/nemo-automodel:26.06.00

2. Navigate to the AutoModel directory (where the recipes are):

$ cd /opt/Automodel

3. Run the recipe:

$ automodel --nproc-per-node=8 examples/llm_finetune/glm/glm_4_9b_chat_hf_squad.yaml

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning

See the LLM Fine-Tuning Guide.