We're Blink Research Labs (https://github.com/BlinkResearchLabs) - an open research collective building AI coding tools in the open. Our philosophy is simple: if it's not open, it's not research; if it's not fast, it's not usable. We think the best AI coding tools shouldn't be locked behind $20/month subscriptions or closed-source walls.
We saw the Sweep model release a few days ago and realized the Neovim ecosystem deserved a complete, local-first, AI coding solution. So we built one.
What makes this different:
- Pure Lua, no external dependencies — No servers, no Node, no Python. Just Lua talking directly to your model backend. This matters when you're waiting for predictions on every keystroke. - Multiple providers — Built-in support for Sweep (1.5B, optimized for next-edit) and Zeta (7B, from Zed Industries). Adding a new provider is ~50 lines of Lua. - LSP-aware context — We fetch definitions and references for the symbol under your cursor and include them in the prompt. The model knows what foo() does before suggesting changes to it. - Backend-agnostic — Works with llama.cpp, Ollama, vLLM, or any OpenAI-compatible server. Bring your own inference.
The plugin sends context-aware prompts based on your cursor position, recent edits, and (optionally) LSP symbols. Predictions render as ghost text inline. We handle all the edge cases: blink.cmp/nvim-cmp menu conflicts, debouncing, streaming, health checks.
Getting started takes 30 seconds:
llama-server -hf sweepai/sweep-next-edit-1.5b-GGUF --port 8000
require("blink-edit").setup({ llm = { provider = "sweep", backend = "openai", url = "http://localhost:8000" } })
The Sweep 1.5B model runs at 200+ tok/s on M-series Macs and fits comfortably on a 4GB GPU. For those with more VRAM, Zeta (7B) gives noticeably better predictions.
This is alpha software - we're iterating fast and want feedback. If you're a Neovim user who's been jealous of Cursor's tab-completion, give this a shot and tell us what breaks.