Using GLM-4 9B on GCP Vertex AI

Implementation guide · GLM-4 · Zhipu AI

ServerlessOpen Source

GCP Vertex AI exposes GLM-4 9B through model ID glm-4-9b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

1
Create an account at GCP Vertex AI and generate an API key.
2
Use the GCP Vertex AI SDK or REST API to call glm-4-9b — see the documentation for request format.
3
You'll be billed $0.10/1M input, $0.10/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install google-cloud-aiplatform

API key

GOOGLE_CLOUD_PROJECT

Model ID

glm-4-9b

For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".

import os
import vertexai
from vertexai.generative_models import GenerativeModel

# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("glm-4-9b")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Type	Price (per 1M)
Input tokens	$0.10
Output tokens	$0.10

Capabilities

No model capability flags are currently sourced.

About GLM-4 9B

GLM-4 9B is Tsinghua Knowledge Engineering Group (THUDM)'s GLM-4 model. It offers a 128K-token context window.

Full model details →

Model Specs

Released2024-06-05

Parameters9B

Context131k

ArchitectureDecoder Only

Google Cloud Platform (GCP)

Mountain View, California, United States