# llama.cpp 服务器新增多模型管理功能

- 来源：Hugging Face：Blog（RSS）
- 发布时间：2025-12-11 23:47
- AIHOT 分数：76
- AIHOT 标记：精选
- AIHOT 链接：https://aihot.news/items/cmoegbhak00a4slxx4drrrsd4
- 原文链接：https://huggingface.co/blog/ggml-org/model-management-in-llamacpp

## 精选理由

本地跑模型终于能像 Ollama 一样热切换，开发调试效率大幅提升

## AI 摘要

llama.cpp 服务器新增了类似 Ollama 的多模型管理功能。该功能采用多进程架构，每个模型独立运行，确保单个模型崩溃不影响其他服务。系统支持自动发现本地 GGUF 模型文件、按需加载，并默认采用 LRU 机制管理最多同时加载4个模型。用户可通过请求中的模型字段路由到特定模型，并可使用 API 进行加载、卸载和列表查看。所有加载的模型可继承路由器的统一设置，也支持通过预设文件为每个模型单独配置参数。内置 Web UI 同样支持模型切换。

## 正文

llama.cpp server now ships with router mode, which lets you dynamically load, unload, and switch between multiple models without restarting.

Reminder: llama.cpp server is a lightweight, OpenAI-compatible HTTP server for running LLMs locally.

This feature was a popular request to bring Ollama-style model management to llama.cpp. It uses a multi-process architecture where each model runs in its own process, so if one model crashes, others remain unaffected.

Quick Start

Start the server in router mode by not specifying a model:

llama-server

This auto-discovers models from your llama.cpp cache (LLAMA_CACHE or ~/.cache/llama.cpp). If you've previously downloaded models via llama-server -hf user/model, they'll be available automatically.

You can also point to a local directory of GGUF files:

llama-server --models-dir ./my-models

Features

Auto-discovery: Scans your llama.cpp cache (default) or a custom --models-dir folder for GGUF files

On-demand loading: Models load automatically when first requested

LRU eviction: When you hit --models-max (default: 4), the least-recently-used model unloads

Request routing: The model field in your request determines which model handles it

Examples

Chat with a specific model

curl http://localhost:8080/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "ggml-org/gemma-3-4b-it-GGUF:Q4_K_M", "messages": [{"role": "user", "content": "Hello!"}] }'

On the first request, the server automatically loads the model into memory (loading time depends on model size). Subsequent requests to the same model are instant since it's already loaded.

List available models

curl http://localhost:8080/models

Returns all discovered models with their status (loaded, loading, or unloaded).

Manually load a model

curl -X POST http://localhost:8080/models/load \ -H "Content-Type: application/json" \ -d '{"model": "my-model.gguf"}'

Unload a model to free VRAM

curl -X POST http://localhost:8080/models/unload \ -H "Content-Type: application/json" \ -d '{"model": "my-model.gguf"}'

Key Options

Flag Description

--models-dir PATH Directory containing your GGUF files

--models-max N Max models loaded simultaneously (default: 4)

--no-models-autoload Disable auto-loading; require explicit /models/load calls

All model instances inherit settings from the router:

llama-server --models-dir ./models -c 8192 -ngl 99

All loaded models will use 8192 context and full GPU offload. You can also define per-model settings using presets:

llama-server --models-preset config.ini

[my-model] model = /path/to/model.gguf ctx-size = 65536 temp = 0.7

Also available in the Web UI

The built-in web UI also supports model switching. Just select a model from the dropdown and it loads automatically.

Join the Conversation

We hope this feature makes it easier to A/B test different model versions, run multi-tenant deployments, or simply switch models during development without restarting the server.

Have questions or feedback? Drop a comment below or open an issue on GitHub.