HN SOTA: Tracking Coding Model Popularity via Hacker News Comments
HN SOTA is a data pipeline that automatically tracks which coding models are popular on Hacker News. It runs daily, scraping the 200 most popular posts from the past 24 hours, then prompts Gemini to filter those whose titles are about LLMs or coding in general (max 50). For each relevant post, it sends the title and comments to Gemini, asking it to identify models from the OpenRouter model list and rate sentiment (positive/negative/neutral) per comment per model.
Results are logged to a public Google Sheet, including comment IDs so you can audit by appending the ID to https://news.ycombinator.com/item?id=. The main page shows a top 10 leaderboard of model mentions over the trailing 10 days, with bar charts scaling to 100%.
The pipeline is designed for transparency – the author explicitly wanted the ability to sanity-check model outputs. Future iterations may scan for harnesses (e.g., Aider, Continue) and hardware setups.
As of May 1, 2026, the aggregate covers April 23 to May 1. The Google Sheet linked from the site gives granular per-comment data.
If you follow model discussions on HN but can't read every thread, this tool gives a quick, automated summary of what's being talked about and how.
📖 Read the full source: HN AI Agents
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