Guide complet du LLM local [2026] : faites tourner une IA sur votre PC
Comment faire tourner un LLM en local sur votre ordinateur. Guide debutant pour Ollama, LM Studio et GPT4All.
Running AI on your own PC without cloud services -- "local LLMs" -- is gaining major traction. Benefits include privacy protection, offline use, and cost savings.
What Are Local LLMs?
Local LLMs are large language models that run directly on your PC or server. Unlike cloud services like ChatGPT, data is never sent externally, ensuring complete privacy.
Benefits
- Privacy: Data never leaves your machine
- Cost: No ongoing fees after setup
- Offline: Works without internet
- Customization: Free model fine-tuning and customization
- Speed: No network latency (fast with GPU)
PC Requirements
Minimum (7B models)
- RAM: 8GB+
- Storage: 10GB+ free
- CPU: Relatively recent (2020+)
- GPU: Not required (CPU inference works)
Recommended (13B-70B models)
- RAM: 16GB+
- GPU: NVIDIA RTX 3060+ (8GB+ VRAM)
- Storage: SSD 50GB+ free
Major Local LLM Tools
Ollama
The easiest way to start with local LLMs. Download and run models with a single command. Available for Mac, Linux, and Windows.
LM Studio
GUI-based local LLM tool for visual model search, download, and execution. Direct Hugging Face downloads and easy parameter adjustment. Most recommended for beginners.
GPT4All
Open-source tool from Nomic AI with a simple chat UI supporting multiple model switching. Includes document loading and RAG capabilities.
Jan
Beautiful UI local LLM client with intuitive model management and conversation. Plugin system for feature extensions.
Recommended Models
General Purpose
- Llama 3.1 8B: Meta-developed, good multilingual support, lightweight
- Gemma 2 9B: Google-developed, well-balanced performance
- Qwen 2.5: Alibaba-developed, strong multilingual performance
Coding
- CodeLlama 7B: Code generation specialized
- DeepSeek Coder: Strong programming support
Lightweight (Low-Spec PCs)
- Phi-3 Mini: Microsoft-developed, 3.8B parameters, lightweight yet capable
- Gemma 2 2B: Google-developed, very lightweight at 2B parameters
Setup (Ollama)
1. Download installer from Ollama's official site 2. Run installation 3. Execute "ollama run llama3.1" in terminal 4. Model auto-downloads and chat begins
Notes
- Local LLMs don't match the latest cloud models (ChatGPT, Claude) in performance
- Larger models need more RAM and GPU memory
- Multilingual quality varies significantly by model
Summary
Local LLMs are ideal for users who prioritize privacy and cost savings. LM Studio or Ollama is the easiest starting point. Begin with a lightweight model and experience AI running on your own PC.