{"version":"1.0","type":"card","id":"942e7bdb-79ba-4186-94d4-5a60a8be050c","url":"https://stacklist.com/card/942e7bdb-79ba-4186-94d4-5a60a8be050c","title":"Best Local LLMs for Consumer GPUs — llama.cpp Guide","source_url":"https://x.com/traffalex/status/2066236717015728227?s=12","note":"This page provides a guide on the best local large language models (LLMs) that can be run on consumer GPUs using llama.cpp. It details models compatible with 8-16GB VRAM, emphasizing ease of use without the need for Docker or Python environments.","image":{"url":"https://ucarecdn.com/83d70e41-bdff-4f6b-8456-70904af20187/","alt":"Best Local LLMs for Consumer GPUs — llama.cpp Guide","width":200,"height":200},"stack":{"id":"df22d380-644b-4775-97bd-5a6e0b42094f","title":"AI inbox","url":"https://stacklist.com/stack/df22d380-644b-4775-97bd-5a6e0b42094f"},"created_at":"2026-06-15T04:19:41.558Z","updated_at":null,"aco":null,"_links":{"self":"/api/public/card/942e7bdb-79ba-4186-94d4-5a60a8be050c.json","html":"https://stacklist.com/card/942e7bdb-79ba-4186-94d4-5a60a8be050c","md":"/api/public/card/942e7bdb-79ba-4186-94d4-5a60a8be050c.md","stack_json":"/api/public/stack/df22d380-644b-4775-97bd-5a6e0b42094f.json"}}