Summary
Fahd Mirza walks through a same-day local installation and test of BLS-Mini-Code-1.0, Cohere’s first dedicated coding model released in June 2026. The model uses a 30-billion-parameter mixture-of-experts architecture with only around 3 billion parameters active at any given moment, giving it strong speed efficiency despite its size. Built-in chain-of-thought reasoning is baked directly into the architecture, and the full model requires approximately 61 GB of VRAM when loaded onto an NVIDIA H100.
The video covers the complete local deployment pipeline: installing prerequisites, pulling the model from Hugging Face, and running inference via Python. Mirza tests it on a demanding front-end task — generating a fully responsive, self-contained HTML tab UI complete with animations, notification badges, and DOM manipulation — and evaluates the output live in a browser. He then extends the experiment by serving the model through vLLM and connecting it to the Hermes agentic coding tool, tasking the pair with refactoring an entire Python application (cert-watch, hundreds of files) into Go.
A practical troubleshooting segment shows how to fix a vLLM context-window misconfiguration that was limiting the model below its 64K maximum. Viewers interested in running frontier-class coding models locally on high-end hardware will find the setup, error resolution, and agentic workflow demonstration directly actionable.
📺 Source: Fahd Mirza · Published June 07, 2026
🏷️ Format: Hands On Build
