Using Llama 3.1-405B on GCP Vertex AI
Implementation guide · Llama 3.1 · AI at Meta
ServerlessOpen Weights
GCP Vertex AI exposes Llama 3.1-405B through model ID llama-3-1-405b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-09. Next refresh: weekly.
Quick Start
- 1
- 2Use the GCP Vertex AI SDK or REST API to call
llama-3-1-405b— see the documentation for request format. - 3
Code Examples
Install
pip install google-cloud-aiplatformAPI key
GOOGLE_CLOUD_PROJECTModel ID
llama-3-1-405bFor 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("llama-3-1-405b")
response = model.generate_content("Hello")
print(response.text)Pricing on GCP Vertex AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $5.00 |
| Output tokens | $16.00 |
Capabilities
JSON / Tool useStructured OutputsFine-tuning
About Llama 3.1-405B
Meta's flagship Llama 3.1 model with 405B parameters and 128K context window. Open-weights model with strong reasoning and coding capabilities.
Model Specs
Released2024-07-23
Parameters405B
Context128k
Knowledge cutoff2024-04