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llama.cpp adds --n-cpu-ffn option for faster dense models on low VRAM

By PulseAugur Editorial · [1 sources] ·

A new pull request for the llama.cpp project introduces the `--n-cpu-ffn` option, designed to improve the performance of dense models for users with limited VRAM. This feature allows a specified number of FFN sublayers to be offloaded to the CPU, similar to the existing `--n-cpu-moe` functionality. The change was submitted by John-194 and aims to make dense models more accessible on lower-end hardware. AI

IMPACT Improves performance for users with limited VRAM when running dense models locally.

RANK_REASON This is a pull request for a specific feature addition to an open-source project, not a major release or significant industry event.

Read on r/LocalLLaMA →

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

llama.cpp adds --n-cpu-ffn option for faster dense models on low VRAM

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This is a pull request for a specific feature addition to an open-source project, not a major release or significant industry event.
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/jacek2023 ·

    llama : add --n-cpu-ffn option by John-194 · Pull Request #26622 · ggml-org/llama.cpp

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vzp4c9/llama_add_ncpuffn_option_by_john194_pull_request/"> <img alt="llama : add --n-cpu-ffn option by John-194 · Pull Request #26622 · ggml-org/llama.cpp" src="https://external-preview.redd.it/bmtIKozP8ayakt…

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