I Tried Replacing Codex With Local LLMs for Magento Coding… Reality Check

Local LLMs are getting insanely good.

For the first time, I was able to generate Magento 2 code locally in agent mode using open source tools like Continue and Cline/OpenCode. The model could read files, split tasks into steps, generate a working module and even partially handle MCP tooling.

That would’ve sounded impossible a year ago.

But after weeks of testing coding models from 20B up to 80B+, I still think people massively underestimate the gap between local models and frontier cloud models like ChatGPT 5.5, Claude Sonnet or Codex.

In this video I tested:

Local coding LLMs with Magento 2 tasks
Continue vs Cline/OpenCode agents
Tool calling and MCP support
VRAM/RAM requirements
Real hardware costs
Why local models still fail at complex debugging
Whether investing thousands into GPUs actually makes sense

My setup:

64GB RAM
RTX 3080 Ti 12GB
Ubuntu + Ollama
Magento 2 development workflow

The biggest problem is not even intelligence anymore.
It’s tooling reliability, context handling and hardware requirements.

To run larger coding models properly you quickly enter:

76GB+ VRAM territory
Multi-GPU setups
Mac Studio ultra expensive configs
Huge electricity consumption

And after all that… cloud frontier models still outperform them by a massive margin in real world development.

Still, the progress over the last year is honestly incredible.
Maybe in 1–2 years this conversation will look completely different.

#ai #llm #localai #magento #opensource #coding #ollama #cline #continue #chatgpt #claude #codex

Видео I Tried Replacing Codex With Local LLMs for Magento Coding… Reality Check канала Vitalii Boiko