AINewsnow

Eksperimen CPU-Only: Membandingkan Dua Build llama.cpp dengan Gemma 4 E2B

This story is from 2026-10-12. It is preserved in the archive; the latest stories are on the live feed.

Aku sangat berminat dengan local LLM, terutamanya bila model bahasa boleh digunakan pada komputer biasa tanpa GPU khusus. Bagi aku, dok semua orang mempunyai workstation dengan GPU mahal. Ada yang hanya menggunakan laptop atau komputer lama. Kalau model masih boleh digunakan untuk menulis dokumen,…

Read the full story at DEV Community — AI ↗

Timeline · 1 report

  1. 2026-10-12 14:39 · DEV Community — AI
    Eksperimen CPU-Only: Membandingkan Dua Build llama.cpp dengan Gemma 4 E2B

More stories

  1. Deploy decision models with llama.cpp on Amazon SageMaker AI — AWS Machine Learning Blog
  2. Qwen3.8-Flash-Next (125B) at ~100 tok/s on an M5 Ultra Mac Studio with llama.cpp — r/LocalLLM
  3. PCIe 4.0 x8/x8 vs x16/x16 for Dual GPUs: Does Bandwidth Choke Local LLM Tensor Parallelism? — DEV Community — Machine Learning
  4. Qwen3.6 35B-A3B optimized for a 4 GB GTX 1050 Ti Mobile: up to 2× prefill and 3× decode vs llama.cpp — r/LocalLLM
  5. strix-llama new branch: prompt processing +21–54% over Vulkan and up to 2.7× over stock ROCm kernel at 128k, same outputs quality — r/LocalLLaMA
  6. Do you actually test open-model inference compatibility? — r/LocalLLaMA
  7. PSA: DeepSeek V4.1 Flash habitually exfiltrates API keys. It is dangerously misaligned and may be hazardous to use — r/LocalLLaMA
  8. Benchmarked 4 Local Models on 3 Harnesses — r/LocalLLM

Get the daily brief of stories like this at 6:30 every morning →