Use Gemini CLI to Deploy Cost-Effective LLM Workloads on GKE
🛠️ Google Cloud demonstrates how the Gemini CLI and GKE Inference Quickstart integrate via the Model Context Protocol (MCP) to streamline selecting, benchmarking, and deploying LLMs on GKE. The post outlines installation steps, example prompts to discover cost and performance trade-offs, and how manifests can be generated for target accelerators. This approach reduces manual tuning and provides data-driven recommendations to optimize cost-per-token while preserving performance.
