nowfound

AI · April 3, 2025

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:…

LocalScore – Local LLM Benchmark launched on April 3, 2025 with 124 votes, #369 of 7,818 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.

Visit localscore.ai ↗Alternativestop 5% of April 2025

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

Download the LocalScore benchmark

There are two ways to run LocalScore. The easiest way to get started is to download one of the Official Models. If you have .gguf models already you run LocalScore with them. localscore-0.9.3.exe -m Llama-3.2-1B-Instruct-Q4_K_M.gguf curl -OL https://localscore.ai/download/localscore-tiny chmod +x localscore-tiny ./localscore-tiny What OS are you running? MacOS/Linux Windows Download LocalScore Open your terminal and run: chmod +x localscore-0.9.3 ./localscore-0.9.3 -m path/to/model.gguf Having issues with the CLI client? Check out the troubleshootingfrom localscore.ai

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…

Does a similar job

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

    Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm

  • AT
    A tool to benchmark LLM APIs (OpenAI, Claude, local/self-hosted)2025 · llmapitest.com · ▲55

    I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…

  • Llmspeed – feel how fast a local LLM runs before you buy the hardware4d ago · llmspeed.dev · ▲329

    Pick hardware and a model, and feel the real speed of a local LLM before you buy. Simulates tokens/sec and time-to-first-token from verified benchmarks for GPUs, Macs, and more.

  • LLM StatsOct 2025 · llm-stats.com · ▲293

    I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…

  • UD
    Unify – Dynamic LLM Benchmarks and SSO for Multi-Vendor Deployment2024 · ▲91

    Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…

  • Deepmark AI2023 · github.com · ▲97

    LLM benchmarking tool for task-specific metrics on your data

More ai this month

the category →
  • Video model that turns script into viral social media videos

    AI · 16d ago · spira.ai

  • The browser where Claude Code and Codex work beside you

    AI · 16d ago · rill.love

  • Solid▲471

    Agents with their own computers, accounts, and budgets.

    AI · 30d ago · solid.tech

  • Kolibri is Aleph Alpha

    AI · 18d ago · tej.as

  • Paintings by AI models: programs run through a simulation of oil paint.

    AI · 19d ago · stillwet.art

  • Onepin▲384

    AI voiceover with every name, price and date said right

    AI · 29d ago · onepin.ai

Source: Show HN post ↗ · launch text quoted in part

Launched alongside, April 2025

the whole month →
  • 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

  • The Unsure Calculator is an online tool that lets you calculate with numbers you’re not sure about.

    Life & fun · 2025 · filiph.github.io

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

    AI · 2025 · github.com

  • Whatting▲898

    The iPad diary, just for you

    Work · 2025 · whatting.com

  • Browser with AI companions that automate web tasks

    AI · 2025 · strawberrybrowser.com

  • Peek▲828

    AI personal finance coach that guides you through decisions

    Work · 2025 · peek.money