LLM-Surgeon v2.0 Released as Offline CLI for Local LLM Hardware Diagnostics

On November 7, 2026 at 14:06, developer Leonel59 posted on DEV Community's AI section about the release of LLM-Surgeon v2.0, a zero-dependency, 100% offline, cross-platform CLI tool built for hardware diagnostics on machines that run LLMs locally. It targets Windows, Linux, and macOS, and the project is hosted as LLM-SURGEON.

The post describes the problem the tool addresses: when users run LLMs locally through Ollama, LM Studio, or llama.cpp, they typically face a familiar guessing game about whether a 30B MoE or 14B dense model will actually fit in VRAM at 16K context, or whether Windows will quietly spill layers into system RAM and tank speed from 55 tok/s to 4 tok/s.

To solve this, LLM-Surgeon v2.0 combines hardware telemetry, GQA KV-Cache math, and NVML data so users can assess how well a model is expected to fit in VRAM before committing to a run. The developer sums up the pitch as surgical local AI hardware diagnostics.

This is the only report received so far on the event. It covers the release and the stated capabilities of the tool, and provides no information yet about later versions, uptake, or follow-up development, so the story currently rests at the initial public announcement.