LLM Reference
GCP Vertex AI

Using Gemini 1.5 Flash 8B on GCP Vertex AI

Implementation guide · Gemini 1.5 · Google DeepMind

Serverless

GCP Vertex AI exposes Gemini 1.5 Flash 8B through model ID gemini-1.5-flash-8b. 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. 1
    Create an account at GCP Vertex AI and generate an API key.
  2. 2
    Use the GCP Vertex AI SDK or REST API to call gemini-1.5-flash-8b — see the documentation for request format.
  3. 3
    You'll be billed $0.04/1M input, $0.15/1M output tokens. See full pricing.
API PortalDocumentationPricing

Code Examples

Install
pip install google-cloud-aiplatform
API key
GOOGLE_CLOUD_PROJECT
Model ID
gemini-1.5-flash-8b

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("gemini-1.5-flash-8b")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

TypePrice (per 1M)
Input tokens$0.04
Output tokens$0.15

Capabilities

No model capability flags are currently sourced.

About Gemini 1.5 Flash 8B

Lightweight 8B variant of Gemini 1.5 Flash optimized for speed and cost-efficiency. Supports 1M token context with fast inference for real-time applications.

Full model details →

Model Specs

Released2024-10-03
Parameters8B
Context1m
ArchitectureDecoder Only
Knowledge cutoff2024-08

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All models on GCP Vertex AI →

Provider

GCP Vertex AI
GCP Vertex AI

Google Cloud Platform (GCP)

Mountain View, California, United States