Last refreshed 2026-05-11. Next refresh: weekly.
Why use Mixtral 8x7B on GCP Vertex AI?
GCP Vertex AI offers Mixtral 8x7B with pay-as-you-go pricing at $0.40/1M 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.
Compare Mixtral 8x7B across 18 providers to find the best fit for your use caseSetup 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")mixtral-8x7bRequest 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("mixtral-8x7b")
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.
Compare Mixtral 8x7B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Databricks Foundation Model Serving | $0.50 | $1.00 |
| NVIDIA NIM | — | — |
| GCP Vertex AI | $0.40 | $1.20 |
| AWS Bedrock | $0.45 | $0.70 |
| OctoAI API (Deprecated) | $0.45 | $0.45 |
Pricing
| 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.
FAQ
What does Mixtral 8x7B cost on GCP Vertex AI?
On GCP Vertex AI, Mixtral 8x7B costs $0.40 per 1M input tokens and $1.20 per 1M output tokens.
What is the context window for Mixtral 8x7B on GCP Vertex AI?
Mixtral 8x7B supports a 32,000 token context window on GCP Vertex AI.
How does GCP Vertex AI compare to other Mixtral 8x7B providers?
Mixtral 8x7B is available from 18 providers. The cheapest input pricing is $0.15/1M tokens from Mistral AI Studio.
Who created Mixtral 8x7B?
Mixtral 8x7B was created by MistralAI as part of the Mixtral model family.
Is Mixtral 8x7B open source?
Mixtral 8x7B is open source under Apache 2.0 according to the seed data.