LLM locaux
argo
Desktop AI agent platform with one-click models and offline-first RAG.
★ 829 étoilesCustom
Voir le guide →Strata est un projet de LLM locaux open source, créé par Niko1221 (Niko1221/Strata sur GitHub). Il compte 33 338 étoiles sur GitHub et 3 565 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 25 octobre 2026.
Strata — one-click Qwen3.8-Flash-Next inference on consumer hardware: chat, code and images, locally, no account, MIT
Installers for Windows and Linux are on the GitHub releases page — the README download badge points at the latest release.
Run the installer, then launch Strata — no account, no sign-up step.
Choose a Qwen3.8-Flash-Next quantisation for your machine (ISTA-DASLab recommended first, Unsloth as an alternative), including the coder build for coding work.
A desktop installer instead of a build-from-source project — download, install, chat.
Multiple quantised builds let the same app run on consumer hardware, with a dedicated coder build for programming.
One app for conversation, coding assistance and image work, all on-device.
Free and open source, usable with your favourite coding tools, with your prompts staying local.
The README download route: the latest release on GitHub.
https://github.com/Niko1221/Strata/releases/latestThe README model guidance: ISTA-DASLab first (including the IQ1_M coder build), then Unsloth quantisations.
https://github.com/Niko1221/Strata#modelsStrata is designed to be used on the desktop and alongside the coding tools you already use, not instead of them.
https://github.com/Niko1221/StrataThe Niko1221 project on GitHub, built around the Qwen3.8-Flash-Next model family.
Yes — MIT licensed, with no account required.
Consumer hardware — the point of the quantised builds is to fit ordinary desktops and laptops; pick a smaller quantisation for weaker machines.
The README recommends ISTA-DASLab builds first, then Unsloth, with a dedicated coder build for programming work.
Download the installer from the latest GitHub release, install, launch, and pick a model build that fits your hardware.
Desktop AI agent platform with one-click models and offline-first RAG.
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