Docker Template Bundling Coding Agents for GPU Cloud Hosting

Melvin Vivas · X post · 2026-09-02 · Open on X

Topics: LLMOps, Deployment & Monitoring, AI Dev Tools & Productivity, Portfolio Projects · Level: intermediate

Summary

Melvin Vivas is using Codex to build a Docker image for GPU hosts like Runpod or QuickPod. The image bundles PyTorch, CUDA, several coding agents (Codex, Claude Code, Pi) and a CUDA-enabled llama.cpp. His reasoning is that coding agents are also good at AI/ML work, so a ready-made GPU environment with them already installed saves setup time.

Key points

• Coding agents can do AI/ML work, so it helps to have them installed next to the GPU.
• Template contents: PyTorch + CUDA, Codex, Claude Code, Pi and CUDA-enabled llama.cpp.
• Built to run on rented GPU hosts such as Runpod and QuickPod.
• Targets the RTX 3090 and other supported GPUs.
• He used a coding agent (Codex) to write the Docker template itself.

Resources mentioned

• Runpod · tool · x.com · paid
  GPU cloud platform for running, training and serving AI models; Flash deploys workloads to it.
  Also in: AI DevBox v1.3.0: a GPU-ready Docker image with coding-agent CLIs (Melvin Vivas on X · notes), Why LLM data agents need solid data foundations (Runpod) (Melvin Vivas on X · notes), Docker image with coding agents pre-installed on a CUDA + PyTorch base (Melvin Vivas on X · notes), GPU devbox Docker image with coding agents on Runpod (Melvin Vivas on X · notes) and 5 more
• QuickPod · tool · console.quickpod.io · paid
  A cloud service for renting GPU pods to host and run your own models.
  Also in: Reusable GPU devbox: PyTorch/CUDA plus six coding agents (Melvin Vivas on X · notes), Self-Host a Coding Model on QuickPod with llama-swap and Use It in Claude Code (Melvin Vivas on X · notes)
• PyTorch · tool · pytorch.org · free · recommended by both Bashiri Smith & Melvin Vivas
  Deep-learning framework. Its built-in scaled dot-product attention (SDP) was the baseline in this benchmark.
  Also in: Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), Wannabe vs $200K+ AI Engineer: RAG, Agents, Context and Fine-Tuning Mistakes (Bashiri Smith on Facebook · notes), AI DevBox v1.3.0: a GPU-ready Docker image with coding-agent CLIs (Melvin Vivas on X · notes), Docker image with coding agents pre-installed on a CUDA + PyTorch base (Melvin Vivas on X · notes) and 5 more
• OpenAI Codex · tool · openai.com · paid
  OpenAI's coding agent. In the diagram it writes code, fixes review findings and drives the build loop. The creator also used it to make this video.
  Also in: An agent bot that installs and drives Codex on its own (Melvin Vivas on X · notes), Asking a Coder bot to install Codex (Melvin Vivas on X · notes), Sign in with ChatGPT: Setting Usage Limits for Each App (Melvin Vivas on X · notes), Codex Cloud Environments Must Be Saved & Published Before Use (Melvin Vivas on X · notes) and 240 more
• Claude Code · tool · code.claude.com · paid · recommended by both Bashiri Smith & Melvin Vivas
  Build agents and pipelines from the terminal; the guide's main agentic coding tool.
  Also in: Create Claude Code Plugins with /plugin-authoring (Melvin Vivas on X · notes), Claude Code mods: customize behavior and UI with plugins (Melvin Vivas on X · notes), AI Engineer Roadmap Overview: From ML Foundations to RAG, Agents & Ops (Bashiri Smith on Facebook · notes), SkillsBento: Free Plugin Marketplace for Codex and Claude Code (Melvin Vivas on X · notes) and 101 more
• Pi · tool · x.com · free
  A customizable coding agent that can be extended through its Extensions API and connected to several model providers.
  Also in: Sign in with ChatGPT: Setting Usage Limits for Each App (Melvin Vivas on X · notes), Pi reaches v1.0 (Melvin Vivas on X · notes), Claude Code mods: customize behavior and UI with plugins (Melvin Vivas on X · notes), Customizing Your Coding Setup with Pi Coding Agent Extensions (Melvin Vivas on X · notes) and 39 more
• llama.cpp · repo · github.com · free
  An open-source C/C++ engine for running GGUF models locally. Its llama-server command provides an OpenAI-compatible HTTP server.
  Also in: Running LLMs Locally Without an Expensive Rig (Melvin Vivas on X · notes), llama.cpp / Llama-macOS v0.5.0 release (Melvin Vivas on X · notes), Run llama.cpp GGUF Checkpoints in Hugging Face Transformers (Melvin Vivas on X · notes), llama.cpp v0.4.1 release announcement (Melvin Vivas on X · notes) and 28 more

Try this

• Build a Docker image for a GPU cloud that comes with PyTorch, CUDA, llama.cpp and coding agents already installed.