The most local LLM efficient vibe coding tool.

Learn how to build an efficient local LLM coding tool to reduce token usage and RAM requirements, using small models for development assistance.

Rust Tokio SQLite FTS5 sqlite-vec Ollama

Overview

Getting out of token while building a project always sucks,specially when we are on an important development phase. Im building kortex coder, which is a coding CLI efficient for Local LLM.
Buying subscription of AI tools are expensive, even they also get out of token. On the other side running big models requires a lot of RAM. Thats why I started building a tool that can use small models efficiently on my pc. Currently It cannot create complex coding solutions and thats not the purpose of it. It can be used as a load reducer on the primary coding tools like claude or antigravity.
I can show it building website using 7B, 14B and 30B parameter models and how it works more efficiently with small models then the other vibe coding tools .

Links

https://github.com/SadidSD/kortex-coder
Rust-based repository `kortex-coder` utilizes PowerShell and Batchfile scripts.

Tech stack

Rust

Rust is a high-performance systems programming language that guarantees memory and thread safety via its compile-time ownership model.

Rust is a statically-typed systems language engineered for performance and reliability, directly challenging C/C++ in speed. Its core innovation is the ownership model and 'borrow checker,' which enforces strict memory and thread safety at compile-time, eliminating data races and null pointer dereferences without a conventional garbage collector. Rust achieves near-native speed through 'zero-cost abstractions,' allowing high-level features to compile into highly optimized code. Major industry players, including Microsoft and Cloudflare, leverage Rust for critical infrastructure, and it is now officially supported for development in the Linux kernel.

https://www.rust-lang.org/

View projects
Tokio

The industry-standard asynchronous runtime for Rust, providing the building blocks for high-performance networking and reliable concurrency.

Tokio delivers a multi-threaded scheduler, a reactor for non-blocking I/O, and specialized timers to handle thousands of concurrent tasks with minimal overhead. It powers mission-critical infrastructure at companies like Discord and AWS (via Firecracker), offering sub-microsecond latency for network services. By leveraging Rust's ownership model, Tokio ensures thread safety while providing high-level abstractions like Channels for MPMC communication and Select for multiplexing asynchronous events.

https://tokio.rs

View projects
SQLite FTS5

A high-performance full-text search engine built directly into SQLite for lightning-fast indexing and prefix matching.

FTS5 transforms SQLite into a robust search engine by implementing a virtual table module that handles complex text queries across massive datasets. It supports advanced features like the BM25 ranking algorithm for relevance scoring, custom tokenizers for specialized languages, and efficient prefix searches using the * operator. By leveraging shadow tables to store inverted indexes, FTS5 allows developers to execute multi-term proximity searches and boolean logic (AND, OR, NOT) with sub-millisecond latency. It is the industry standard for adding local, offline search capabilities to mobile apps and desktop software without the overhead of external services like Elasticsearch.

https://www.sqlite.org/fts5.html

View projects
sqlite-vec

A lightweight, zero-dependency SQLite extension written in C that brings fast, local vector search directly to your embedded database.

SQLite-vec is a cross-platform SQLite extension designed to handle vector search locally, eliminating the need for complex, external vector database infrastructure. Written in pure C with zero dependencies, it runs efficiently on everything from mobile devices and Raspberry Pis to web browsers via WebAssembly (WASM). Developers can store embeddings, run K-Nearest Neighbor (KNN) similarity queries, and manage metadata entirely within a single SQLite file using standard SQL syntax. It is an ideal fit for edge AI deployments, local Retrieval-Augmented Generation (RAG) pipelines, and serverless applications that require simple, offline-first vector operations.

https://github.com/asg017/sqlite-vec

View projects
Ollama

Deploy and run open-source Large Language Models (LLMs) like Llama 3 and Mistral locally on your machine: achieve private, cost-effective AI via a simple command-line interface.

Ollama is the essential tool for running LLMs locally: consider it the Docker for AI models. It packages complex models and dependencies into a single, easy-to-use application for macOS, Linux, and Windows systems. You get immediate access to models like Gemma 2 and DeepSeek-R1 via a straightforward CLI or REST API. This local-first approach guarantees data privacy and security, eliminating cloud dependency and high API costs. Ollama also optimizes performance on consumer hardware using techniques like quantization, ensuring efficient execution even on standard desktops.

https://ollama.com

View projects

The most local LLM efficient vibe coding tool.

Related talks