Benchmarks

Each report is a snapshot of what the community is actually saying about one model, sampled from public posts and comments on the source subreddit — the top posts of the past month and the comments underneath them. Nothing here is benchmarked in a lab: the scores reflect reported experience, so they track what practitioners hit in real use, complaints included.

Every model is scored across the same ten categories — intelligence, speed, coding quality, instruction following, long context, price/value, reliability & uptime, creativity & writing, multimodal & vision, and agentic & tool use — plus an overall score out of 100. Where a category has no usable data in the sample, it is left empty rather than guessed.

Each report also carries a confidence level — low, medium or high — with a note explaining how much signal the sample contained, so you can weigh a score built from hundreds of sampled posts against one built from a few dozen. The three families cover open and local models (r/LocalLLaMA), frontier lab releases (r/singularity) and coding-model rankings (r/codex).