» Tag
llama.cpp
13 postsWhy reformatting prompts beats quantization for CPU LLM inference
Measured on a free ARM CPU box: rewriting prompts as label:value fact sheets cut LLM prefill time 6.5x while quantization tricks hurt accuracy.
9.9x Lower TTFT on Real Android Phone via llama.cpp KV Reuse
EdgeSync-LLM reuses llama.cpp's public KV APIs to skip reprocessing shared prefixes, cutting Android TTFT 9.9x while catching a fake 8.8x speedup.
Tesla P100's silent FP16 precision bug in llama.cpp fixed
A 3-line CUDA patch in llama.cpp fixes a years-old silent FP16 precision bug on Tesla P100 GPUs, with zero performance cost.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comApple Silicon macOS VMs Get 11-16x Faster LLM Inference via Llama.cpp
Cua's Metal capability shim delivers 11-16x faster llama.cpp LLM inference in macOS VMs on Apple Silicon, with open benchmarks and source.
llama.cpp Adds Lossless F32 Compression via QFX32/QFX16
llama.cpp PR adds QFX32/QFX16 GGUF formats that losslessly compress F32 models by 2.05x with bit-identical weight reconstruction.
Quantprobe Runs a 110B-Parameter LLM on a 16GB RAM 2016 Desktop
Quantprobe shows how careful memory-tier placement lets a 2016 desktop with 16GB RAM run a 110B-parameter LLM, validated with pre-registered predictions.
MoE Expert Streaming Runs a 120B-Parameter LLM on an Android Phone
An open-source Android app streams MoE experts from flash storage to run a 120B-parameter LLM on phone CPUs, with 30B models at usable speeds.
Local Model Showdown Round 9: Qwen 3.6, Nemotron, Qwythos Coding Test
Five LLMs face off on a real coding task via llama.cpp on an RTX 5090 in Round 9 of the Local Model Showdown series.
Intel Arc B70 32GB Runs Qwen3.6-35B-A3B at 130 t/s via Vulkan
Benchmark: Intel Arc Pro B70 32GB runs Qwen3.6-35B-A3B via llama.cpp Vulkan at ~130 t/s (4-bit, 262k ctx) and ~69 t/s hybrid 8-bit offload.
Speculative Decoding: The Free Speedup Most Local LLM Setups Skip
Speculative decoding speeds up local LLM inference 1.5-2.5x with identical output; 2026 saw it built into models via multi-token prediction.