GCP Vertex AI exposes Chat Bison through model ID chat-bison-001. 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
- 2Use the GCP Vertex AI SDK or REST API to call
chat-bison-001— see the documentation for request format. - 3
Code Examples
pip install google-cloud-aiplatformGOOGLE_CLOUD_PROJECTchat-bison-001For 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("chat-bison-001")
response = model.generate_content("Hello")
print(response.text)Pricing on GCP Vertex AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $0.50 |
Capabilities
About Chat Bison
Chat Bison, a large language model from Google, is adept at multi-turn conversations, excelling in language understanding and generation for interactive applications. Although details about its architecture are limited, it is based on Google's PaLM 2 framework and trained on extensive text and code datasets. This model is proficient in various language tasks, including code and text generation, editing, and problem-solving, and is particularly well-suited for multilingual content and handling synonymous inquiries in FAQ systems.