LLaMA.cpp users seek long-context and KV cache optimization

A user on the r/LocalLLaMA subreddit is seeking advice on optimizing the llama.cpp framework for handling long contexts and efficient KV cache quantization. They are currently using a modified version of llama.cpp with MTP (Multi-Threaded Processing) and a Q4 cache, achieving around 60 tokens per second with shorter contexts, but experiencing a significant drop in speed as the context length increases. The user is looking for alternative methods or configurations that offer better performance for extended context windows. AI

IMPACT Users are exploring ways to improve the performance of local LLM inference for longer contexts.

RANK_REASON User question on a forum about optimizing existing software, not a new release or significant event.

Read on r/LocalLLaMA →

• llama.cpp
• vllm

• infra
• other

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