Local LLM Picker

Find which local small model actually works for your GPU

Problem

Developers with consumer GPUs (e.g., 24GB VRAM) want to run small coding models but have no idea which of the many options like Qwen3-Coder-30B or DeepSeek-Coder-V2-Lite performs best on their hardware and task.

Solution

A local benchmarking tool that detects hardware, runs a set of coding tasks (completion, explanation, refactoring) on candidate models on the user's machine, and produces a comparable report of accuracy and speed with recommendations.

Users

Individual developers with consumer GPUs, small teams making tech stack decisions

MVP

Auto-detect GPU VRAM and RAM; 10 built-in coding tasks; support 3-5 popular small models with quantization variants; output pass rate and tokens/sec table; one-click share report.

Revenue

Open-source core; paid cloud sync for history, team leaderboards, and a regularly updated model compatibility database.

Why now

The local small model ecosystem is exploding, but selection info is fragmented and cloud benchmarks don't reflect individual hardware; this is a gap indie developers can fill.