---
title: "I Will Deploy Hugging Face LLMs to GCP Vertex AI or Cloud Run"
url: https://zinnhub.com/zinns/deploy-hugging-face-models-llama-mistral-gemma-on-gcp/
description: "Get your Hugging Face model — Llama, Mistral, Gemma, or BERT — deployed to a secure, scalable, production-ready endpoint on Google Cloud, fully containerised and API-ready."
published: 2025-12-21T23:16:45+00:00
modified: 2026-07-01T01:02:59+00:00
language: en-GB
---

# I Will Deploy Hugging Face LLMs to GCP Vertex AI or Cloud Run

You have found the right model. Now you need it running reliably in production — not just locally, not in a notebook, but behind a secure, scalable API your application can actually call.

That is exactly what this service delivers.

Zinn Digital are Google Cloud experts based in London. We take your chosen Hugging Face model and deploy it to a production-ready environment on Vertex AI or Cloud Run — fully containerised, GPU-provisioned, and protected behind a secure, VPC-native endpoint. When the work is done, you receive a live API you can immediately integrate into your product.

\*\*What makes this different from “just running a script”\*\*

Anyone can spin up a GPU instance and hope for the best. We assess your model’s actual RAM and VRAM requirements before a single line of code is written, select the right GPU tier (T4, L4, or A100) to balance cost and latency, and build infrastructure that scales with your workload rather than falling over under it. Every deployment is secured by design — no public endpoints left open, no credentials hardcoded.

\*\*How it works\*\*

First, send us the model link and a brief description of your use case. We assess the model’s resource requirements and confirm the deployment approach. We then containerise the model using Docker, deploy it to Vertex AI or Cloud Run, configure GPU provisioning and API security, and finally hand you a working Python test script so you can verify the endpoint yourself.

\*\*What is included\*\*

Depending on the tier you choose, you will receive some or all of: an expert consultation and architecture assessment, full model deployment to a secure GCP endpoint, source code for the containerisation and deployment pipeline, and detailed inline code comments so your team can maintain and extend the work confidently.

\*\*Who this is for\*\*

This service suits developers and engineering teams who have identified a Hugging Face model they want to use in production but lack the GCP infrastructure experience to deploy it safely and efficiently. It is equally well suited to technical founders who need a working AI backend without hiring a full cloud team, and to organisations already using Google Cloud who want expert hands on a specific deployment challenge.

\*\*Before you order\*\*

Every project is unique. Model size, GPU requirements, existing GCP architecture, and security constraints all vary. Please send a message before placing your order so we can confirm the approach is right for your situation and agree on scope. This ensures the work starts on the right footing and there are no surprises.