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Self-hosting Ollama limited by hardware, user notes performance gaps

A user is self-hosting Ollama on their system but is limited to smaller models like llama3.1:8b due to the lack of a dedicated GPU. While llama3.1:8b is functional, the user notes that larger models such as Gemini and Claude offer superior performance, though all LLMs can still provide incorrect or outdated information. AI

IMPACT Highlights hardware constraints for running advanced LLMs locally and the performance disparity between smaller and larger models.

RANK_REASON User commentary on LLM performance and self-hosting limitations.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Self-hosting Ollama limited by hardware, user notes performance gaps

COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · RockyC ·

    @ nickstar I also only use the free tier of the LLMs. I am self-hosting ollama, but I'm limited to models like llama3.1:8b until I can get a dedicated GPU. Llam

    @ nickstar I also only use the free tier of the LLMs. I am self-hosting ollama, but I'm limited to models like llama3.1:8b until I can get a dedicated GPU. Llama3.1:8b is not too shabby, but Gemini and Claude run rings around it. But all of them will still CONFIDENTLY give you wr…