On-device model that explains what changed. Give it a commit and Knot Delta writes a grounded report: what moved, why, and the risk. A 9B model, served as a single quantized GGUF that runs on your machine.

Part of the Knot AI family, alongside Knot Scribe (which writes your commit messages). Delta is the change-intelligence layer inside Knot.

A fine-tune of Qwen3.5-9B, merged and exported to a text-only Q4_K_M GGUF (~5.2 GB) for llama.cpp / Ollama.

Every number is measured against objective ground truth (real git history), reported beside the baseline a lazy model would score. No aggregate "intelligence score" is quoted. Frozen held-out set: 325 commits across 9 unseen real repos (vite, vue, svelte, astro, ionic, gumroad, OpenDream, radicle, vllm).

Multi-repo generalization (exact-line precision, 4 unseen repos):

Honest read: Delta never cites a file that isn't in the diff (100% across every repo, including Go, which is absent from its training data), and it always points at the right region. What it does not yet do reliably is pin the exact line — that lands 52–74% of the time, lowest on Rust. It knows which file and which part changed; the precise line is still improving. One capability, measured straight, with the parts that don't yet work said out loud.