This article details a step-by-step guide for deploying the Gemma 4 E2B model on Google Cloud Run, utilizing an NVIDIA L4 GPU. The deployment is managed by a Python MCP server, which has been updated to use the MCP SDK 2.x. This setup allows for automated staging of model weights, service deployment, health checks, and benchmarking, with Cloud Run providing a serverless environment that scales to zero when idle. AI
IMPACT Provides a practical guide for deploying LLMs on cloud infrastructure, potentially lowering the barrier for developers.
RANK_REASON Article provides a technical guide for deploying an existing model with specific infrastructure and tools.
Read on dev.to — Claude Code tag →
- aisprint-491218
- Claude Code
- Cloud Run
- Gemma 4
- Google Cloud SDK
- Google Cloud Storage
- MCP SDK 2.x
- NVIDIA L4
- Python
- vLLM
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