LocalCoder

What it does

LocalCoder matches your hardware to the best local coding AI model. Pick your platform (Apple Silicon, NVIDIA, or CPU), select your chip and memory, and get the right model, quantization, speed estimate, and copy-paste commands to start coding locally. No more digging through Reddit threads. No more VRAM guesswork. Built from real data — HN benchmarks, Unsloth tables, llama.cpp results. Free: Top pick + Ollama commands Pro ($9): Alternatives, llama.cpp, IDE setup

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  1CodeJan 2026 · github.com · ▲569

  Just to clarify the background a bit. This project wasn’t planned as a big standalone release at first. On January 16, Ollama added support for an Anthropic-compatible API, and I was curious how far this could be pushed in practice. I decided to try plugging local Ollama models directly into a Claude Code-style workflow and see if it would actually work end to end. Here is the release note from Ollama that made this possible: https://ollama.com/blog/claude Technically, what I do is pretty straightforward: - Detect which local models are available in Ollama. - When…

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  Ollama v0.19Apr 2026 · ollama.com · ▲410

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  Find the best local LLM for your hardware, ranked by benchmarksMay 2026 · github.com · ▲283

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  LocalScore – Local LLM Benchmark2025 · localscore.ai · ▲124

  Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…

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