# zai-org/glm-4-9b-hf — vLLM serving recipe

> GLM-4 9B dense base language model with 8K context.

Configuration: hardware `xeon6` (4× Xeon 6) · strategy `single_node_tp` (Tensor Parallel) · variant `default` (BF16)

- Interactive page: https://vllm-recipes-cimvhk5sf-inferact-inc.vercel.app/zai-org/glm-4-9b-hf
- This configuration as JSON: https://vllm-recipes-cimvhk5sf-inferact-inc.vercel.app/zai-org/glm-4-9b-hf.json?hardware=xeon6

The commands below were rendered for exactly this configuration and take precedence over any example in the guide.

## Other configurations

Change the query string (the same parameters as the page URL) and fetch this URL again. Unknown or incompatible values fall back to the recipe default, so check the Configuration line.

- `hardware`: `xeon6`
- `variant`: `default`
- `strategy`: `single_node_tp`, `multi_node_tp` (multi-node strategies also need `nodes=<n>`)

## Install

Requires vLLM >= 0.6.5.

Docker image: `vllm/vllm-openai-cpu:latest-x86_64`

## Serve

```bash
vllm serve zai-org/glm-4-9b-hf \
  --tensor-parallel-size 1
```

Docker equivalent:

```bash
docker run --shm-size=16g \
  --privileged --ipc=host -p 8000:8000 \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  vllm/vllm-openai-cpu:latest-x86_64 zai-org/glm-4-9b-hf \
  --tensor-parallel-size 1
```

## Guide

> Background reference. Commands in it are examples and may target another configuration — use the Serve section above.

### Overview

GLM-4-9B is the dense base model in the GLM-4 9B family. Intel Xeon 6 CPU
serving was validated with BF16.

### Prerequisites

- Hardware: Intel Xeon 6/Xeon 5 CPUs
- vLLM >= 0.6.5

#### Docker (Intel Xeon 6 CPUs)

```bash
docker pull vllm/vllm-openai-cpu:latest-x86_64
```

### Intel Xeon 6

```bash
vllm serve zai-org/glm-4-9b-hf \
  --tensor-parallel-size 1
```

Docker (the image entrypoint is `vllm serve`):

```bash
docker run \
  --privileged --ipc=host -p 8000:8000 \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  vllm/vllm-openai-cpu:latest-x86_64 zai-org/glm-4-9b-hf \
  --tensor-parallel-size 1
```

The example uses TP=1. Adjust TP/DP for the deployment topology;
host-specific CPU placement is intentionally not hard-coded.

### Runtime and Platform Tuning

The following settings are intentionally not prescribed as portable CPU model
defaults because they depend on the workload, hardware, or runtime environment:

- `--max-num-batched-tokens`: scheduler/throughput tuning.
- `--max-num-seqs`: concurrency and scheduler-capacity tuning.
- `--gpu-memory-utilization`: platform memory-budget tuning.
- `--no-enable-prefix-caching`: workload/benchmark cache-policy tuning.
- `VLLM_ENGINE_ITERATION_TIMEOUT_S`: operational runtime timeout.

These settings may still appear in validated hardware-specific overrides. Tune
them at deployment time based on platform resources, workload shape, and
latency/throughput goals.

### References

- [Model card](https://huggingface.co/zai-org/glm-4-9b-hf)
- [vLLM CPU installation](https://docs.vllm.ai/en/latest/getting_started/installation/cpu/)