A user on the r/LocalLLaMA subreddit is seeking methods to improve prompt processing speed for large language models, specifically mentioning issues with Qwen and a significant drop in tokens per second as context length increases. They are currently using Linux with Vulkan and note that while HIP offers a speed boost, it comes with increased memory usage and poor token generation. The user is looking for solutions to maintain higher processing speeds during long agentic runs. AI
RANK_REASON User-generated question on a niche subreddit about optimizing local LLM performance.
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