Quick Start
- 1
- 2Use the GCP Vertex AI SDK or REST API to call
mixtral-8x7b— see the documentation for request format. - 3
Code Examples
pip install google-cloud-aiplatformGOOGLE_CLOUD_PROJECTmixtral-8x7bFor 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("mixtral-8x7b")
response = model.generate_content("Hello")
print(response.text)About GCP Vertex AI
Google Cloud Vertex AI is a comprehensive machine learning platform that provides end-to-end solutions for developing, deploying, and managing AI models. The platform offers a unified interface that integrates various tools and services, enabling users to efficiently handle the entire machine learning lifecycle. Key features include AutoML capabilities for building custom models with minimal coding, a managed notebook environment for prototyping, and robust MLOps tools for model monitoring and versioning. Vertex AI supports both pre-trained models and custom training, making it versatile for a wide range of applications such as natural language processing, image recognition, and predictive analytics. The platform's design focuses on increasing productivity and accelerating time-to-market for AI solutions. By consolidating multiple AI tools into a single ecosystem, Vertex AI reduces manual effort and enhances collaboration among data scientists and engineers. Its scalable architecture allows organizations to efficiently manage large datasets and complex models, while the pay-as-you-go pricing model makes it accessible for businesses of all sizes. Additionally, Vertex AI's integration with popular open-source frameworks like TensorFlow and PyTorch enables users to leverage existing models and tools, fostering innovation and facilitating the development of customized AI applications tailored to specific business needs.
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.
Pricing on GCP Vertex AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.40 |
| Output tokens | $1.20 |
Capabilities
No model capability flags are currently sourced.
About Mixtral 8x7B
Mixtral 8x7B, developed by Mistral AI, features a cutting-edge Mixture of Experts (MoE) architecture, utilizing eight experts with seven billion parameters each, yielding a total of 46.7 billion parameters. This architecture activates only two experts per token, allowing for efficient processing and a 6x faster inference rate compared to Llama 2 70B. The model excels in performance, surpassing Llama 2 70B and competing with GPT-3.5 on numerous benchmarks. It supports multiple languages and can handle context up to 32,000 tokens, enhancing understanding of lengthy text. Designed for diverse tasks, it is strong in code generation and available under a permissive Apache 2.0 license, promoting community engagement. Compatible with various optimization tools, its weights are easily deployable, with Mistral AI continuing to improve its capabilities through performance optimizations and fine-tuning efforts.