LocalLLaMA seeks monthly real-world local LLM performance data

This is the right instinct for local-first adoption, but it only becomes useful if submissions are normalized and reproducible.

• –The requested fields map to what developers actually need for deployment decisions: tokens/sec, latency feel, and context behavior on specific hardware.
• –Community benchmark projects already exist, but many still struggle with apples-to-oranges comparisons across stacks and quantization settings.
• –A monthly cadence could make this more actionable than static leaderboards, especially as model releases and inference runtimes change quickly.
• –With zero comments so far, the biggest risk is low sample density and strong self-selection bias from power users.