nowfound

AI · April 3, 2025

LL

LocalScore – Local LLM Benchmark

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:…

In plain words

LocalScore is an open-source benchmarking tool for measuring the performance of local large language models on various hardware configurations. Built as a command-line interface using Llamafile, it works across different operating systems and hardware setups. The accompanying website provides a searchable database of benchmark results, letting users compare how different models perform. It's designed for developers and researchers interested in running AI locally who need reliable performance data to guide their hardware and model choices.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

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: https://localscore.ai - Demo video: https://youtu.be/De6pA1bQsHU - Blog post: https://localscore.ai/blog - CLI Github: https://github.com/Mozilla-Ocho/llamafile/tree/main/localsco... - Website Github: https://github.com/cjpais/localscore

More ai this month

the category →
  • I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

    AI · 16d ago · simedw.com

  • Astute585

    Automate your B2B brand going viral, with new media creators

    AI · 18d ago · company-app.joinastute.com

  • Grok Bot547

    AI teammates that you can give real work to

    AI · 25d ago · x.ai

  • Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 26d ago · cactuscompute.com

  • Make your software self-driving

    AI · 30d ago · coldtea.ai

  • Soloop472

    Approval-first Agent OS for solo founders

    AI · 30d ago · soloop.io

Launched alongside, April 2025

the whole month →
  • IB

    Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…

    Dev tools · 2025 · runpyxl.com

  • UC

    Life & fun · 2025 · filiph.github.io

  • IB

    https://the-pocket.github.io/Tutorial-Codebase-Knowledge/

    AI · 2025 · github.com

  • Whatting898

    The iPad diary, just for you

    Work · 2025 · whatting.com

  • AI browser that saves you 18h/week

    AI · 2025 · strawberrybrowser.com

  • Peek828

    AI personal finance coach that guides you through decisions

    Work · 2025 · peek.money