AI Guide to the Galaxy Episode 2: Running Local LLMs with Docker Model Runner
In this episode of AI Guide to the Galaxy, Principal Engineer Jacob Howard joins Oleg for a deep dive into Docker Model Runner, the open-source tool that brings large language models (LLMs) to your local Docker CE and Docker Desktop environments.We cover:
✅ How to install and run Docker Model Runner on Docker CE
✅ GPU vs. CPU support, container-based architecture & runtime logic
✅ Running LLMs in CI environments like GitHub Actions
✅ Benchmarking performance on lightweight setups (e.g. 1 CPU, 16GB RAM)
✅ Selecting model sizes and quantizations for your hardware
✅ Using Model Runner in Kubernetes and Google Cloud Run
✅ Debugging with logs, Docker Desktop's new request inspector, and OpenAI API compatibility
✅ Upcoming features: VLLM backend support, multimodal inference, and more
Whether you're building agentic applications, experimenting with LLMs on Raspberry Pi, or deploying production-scale AI in Kubernetes—this episode will guide you through it.
🧠 Mentioned Tools & Concepts:
- Docker CE & Docker Desktop
- Docker Model Plugin
- LLaMA.cpp (Llama C++)
- Quantized LLMs & VRAM sizing
- OpenAI-compatible APIs
- OCI model artifacts
- Kubernetes YAML for AI workloads
🔗 GitHub Repos:
model-runner: https://github.com/docker/model-runner
model-cli: https://github.com/docker/model-cli
model-distribution: https://github.com/docker/model-distribution
👉 Don’t forget to like, subscribe, and hit the bell to stay in the loop for upcoming episodes!
#docker #ai #podcast #dockermodelrunner #llm #genai #softwaredevelopment #devops #aidevelopment #dockerpodacst Receive SMS online on sms24.me
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