Headroom vs Knoku

It also checks your driver for the subgroup bug that makes some in-browser LLMs produce garbage.

Knoku turns your docs into an AI assistant your users can actually talk to.

About Headroom

It also checks your driver for the subgroup bug that makes some in-browser LLMs produce garbage. One outbound request: ~0.4 MB of public model metadata to derive bytes per token, no run data attached. Projections are measured read bandwidth ÷ bytes touched per token, at empty context; derived manifests make bytes-per-token exact, estimates fall back to an honest band. Real engines land below the ceiling; the gap is engine overhead (see methodology). Runs the transformers.js WebGPU path on the exact model your ceiling is quoted for ( onnx-community/gemma-4-E2B-it-ONNX.

About Knoku

Knoku turns your docs into an AI assistant your users can actually talk to. Answer everywhere with citations, and see what your docs are missing. Track deflection, traffic, repeated questions, and knowledge gaps in one place. See how many questions were answered before they became tickets, across every channel. Find the repeated questions and knowledge gaps your team should fix next. Track where users ask from and which channels create the most support demand. GitHub sync Connect a GitHub repo and sync Markdown docs into your index, kept current on each commit, with citations back to the file on GitHub.