# 0xSojalSec/LLMs-local

list of awesome platforms, tools, and resources   run for LLMs locally

Repository: https://github.com/0xSojalSec/LLMs-local
Canonical: https://ross.abutalabs.com/products/llms-local
License Family: other
Last push: 2026-06-10T20:19:16+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 86, release rhythm 35, longevity 18
- inputs: {"age_days": 259, "days_push": 84, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1087, forks 126 (observed 2026-08-28T04:03:32.365423+00:00)

## What it is
A curated awesome-list of platforms, tools, models, and resources for running large language models locally. It covers inference engines, UIs, agent frameworks, RAG, fine-tuning, hardware, and tutorials.

## Use cases
- find tools to run llms locally
- compare local llm inference engines like ollama and llama.cpp
- discover offline chatgpt alternatives
- find agent frameworks and rag tools for local models
- learn how to fine-tune models on my own hardware
- pick hardware for a local llm rig

## When to choose
- you want a curated starting point for the local LLM ecosystem
- you need to discover tools across inference, agents, RAG, and hardware in one place

## When to avoid
- you need runnable software rather than a list of links
- you need a maintained tool with a license and support rather than a reference list

## Facets
- artifact type: learning-resource
- maturity: active
- function: llm-inference, rag, agent-framework, mcp, llm-training, developer-tools
- domain: large-language-models, artificial-intelligence, self-hosted, awesome-lists, tutorials
- platform: cross-platform, self-hosted
- tags: awesome-list, local-llm, curated-resources, inference, offline-ai, gpu

## Member repositories
- 0xSojalSec/LLMs-local (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:32.365423+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:49:24.826169+00:00, confidence not recorded.
  - readme: https://github.com/0xSojalSec/LLMs-local (fetched 2026-08-28T04:03:32.365423+00:00, sha 3e2ba4d0b6e4)
- Data as of 2026-08-30T08:39:29.467469+00:00.