Last refreshed 2026-06-15. Next refresh: weekly.
Why use Text Bison on GCP Vertex AI?
GCP Vertex AI offers Text Bison with pay-as-you-go pricing at $0.50/1M input tokens. Vertex AI is Google Cloud's managed AI platform, offering access to Gemini models and hundreds of partner models alongside tools for fine-tuning, grounding, vector search, and end-to-end MLOps pipelines.
Setup recipe
Python + curlpip install google-cloud-aiplatformexport GOOGLE_CLOUD_PROJECT=...import os
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")text-bison-001Request example
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("text-bison-001")
response = model.generate_content("Hello")
print(response.text)Gotchas
- 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".
- The examples expect GOOGLE_CLOUD_PROJECT; rename it only if your application config maps the new variable.
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $0.50 |
Capabilities
About Text Bison
Text Bison is an advanced language model developed by Google AI as a refined iteration of the Pathways Language Model (PaLM) 4. It is particularly effective at handling a range of natural language processing tasks, including classification, sentiment analysis, entity extraction, question answering, summarization, and text rewriting 5. The model boasts a substantial token limit, initially set at 4096, later expanded to 32,000, allowing it to process longer texts compared to some earlier models 3.