가이드로
RUNTIME / MEDIUM

llama.cpp

GGUF models, CPU/GPU offload, embedded and unusual hardware

1차 출처
DifficultyMediumSetup profile
Platforms5cpu · apple · nvidia · amd · intel
APIOpenAI-compatible server:9931 default
01 / INSTALL & RUN

Installation depends on your OS. These commands are examples or templates: replace placeholders and verify quantization, file format, drivers and runtime support. Memory fit does not guarantee deployment.

  1. 1
    Installbrew install llama.cpp # or use upstream binaries
  2. 2
    Start a modelllama-server -m <downloaded-model.gguf> --ctx-size <verified-context> --port 9931
  3. 3
    Connect your app

    OpenAI-compatible server · :9931 default. Keep the service bound to localhost unless you add authentication and network controls.

주의

New architectures may require a recent build. Backend availability does not imply equal performance. Since v0.7.0 (2026-10-15) llama-server listens on port 9931 by default instead of 8080; the example commands pin that port explicitly. Older builds accept the same --port flag but default to 8080.

02 / COMPATIBLE MODELS

대표 오픈 웨이트 모델

Alibaba Qwen

Qwen3.6 27B

27BQ4 / NVFP4 estimate
추정 메모리
~18.5 GB
컨텍스트
262K native
Alibaba Qwen

Qwen3.8 27B

27BQ4 estimate
추정 메모리
~19.5 GB
컨텍스트
262K native
Alibaba Qwen

Qwen3.6 35B-A3B

35B3B active · Q4 / NVFP4 MoE
추정 메모리
~25 GB
컨텍스트
262K native
DeepSeek

DeepSeek V4 Flash

284B13B active · Official FP4 + FP8 mixed
추정 메모리
~176 GB
컨텍스트
1M native
Google

Gemma 3 1B

1BINT4 / GGUF Q4
추정 메모리
~1.4 GB
컨텍스트
32K
Meta

Llama 3.2 3B

3BGGUF Q4
추정 메모리
~2.8 GB
컨텍스트
128K