Guide: Deploy Gemma 4 2B on Cloud Run with NVIDIA L4 GPU Using Python MCP Tools

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A step-by-step deployment guide has been published for running Google's Gemma 4 2B model on Google Cloud Run using an NVIDIA L4 GPU and vLLM as the inference server. The project includes a single-file Python MCP server that handles model weight staging, service deployment, health checks, benchmarking, and teardown. Cloud Run's serverless architecture eliminates the need to provision VMs or install GPU drivers manually, with the service scaling to zero when idle. The guide also covers a required migration to MCP Python SDK 2.x after a version-unbound pip install broke the server's import on fresh setups. Prerequisites include Python 3.10 or newer, Claude Code, the Google Cloud SDK with active credentials, and a GCS bucket for storing model weights.

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