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Programmers Share Workflows for Slow Local LLM Coding

Programmers are discussing strategies for using local large language models (LLMs) when their hardware can only generate tokens at a slow rate, below 10 tokens per second. The conversation on Reddit's r/LocalLLaMA subreddit focuses on optimizing workflows and identifying the most effective methods for coding assistance under these performance constraints. Users are sharing their personal approaches and seeking advice on how to best leverage LLMs despite slow generation speeds. AI

IMPACT Discusses practical challenges and solutions for developers using local LLMs with limited hardware capabilities.

RANK_REASON User discussion on a subreddit about optimizing workflows for slow local LLM performance.

Read on r/LocalLLaMA →

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

Programmers Share Workflows for Slow Local LLM Coding

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/segmond ·

    For programmers with slow local LLM setup, what's your workflow?

    <!-- SC_OFF --><div class="md"><p>What's your workflow and what's the best way you have found to code with local LLM when your token generation is &lt; 10 tk/sec?</p> </div><!-- SC_ON --> &#32; submitted by &#32; <a href="https://www.reddit.com/user/segmond"> /u/segmond </a> <br …