FastAPI Powering Gemini: Building a Scalable Inference API on Cloud Run

infrastructure #llm 📝 Blog|Analyzed: Feb 14, 2026 03:41•

Published: Feb 2, 2026 07:35

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1 min read

Analysis

This article details a practical approach to deploying a [LLM] inference API using FastAPI and Google Cloud Run. The focus on leveraging asynchronous communication with FastAPI for speed and the clear project structure design provides a valuable blueprint for developers looking to integrate [Generative AI] capabilities into their applications.

Key Takeaways

•The project leverages FastAPI for its speed and asynchronous capabilities.
•Deployment targets Google Cloud Run for scalability.
•The article provides a detailed structure for local development and staging environments.

Reference / Citation

View Original

"FastAPI is selected because of its faster, lightweight asynchronous communication compared to Django, its affinity with Python, and personal interest."

Zenn GeminiFeb 2, 2026 07:35

* Cited for critical analysis under Article 32.

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FastAPI Powering Gemini: Building a Scalable Inference API on Cloud Run