The Best Local AI Stack for 2025
Run LLMs, vision models, and embeddings on your own hardware. Zero API cost, full privacy, works offline.
$0API cost
100%Data stays local
OfflineAfter download
Run LLMs, vision models, and embeddings on your own hardware. Zero API cost, full privacy, works offline.
Data never leaves your device. Essential for HIPAA, GDPR, and confidential business data.
Once models are downloaded, everything runs without internet. Perfect for air-gapped environments.
No per-token billing. Run unlimited inference on hardware you already own.
No network round-trip. Response starts immediately from local GPU. Sub-100ms first token.
Run any open-weight model: Llama 3, Mistral, Gemma, Qwen, DeepSeek. No provider lock-in.
Windows, macOS (Apple Silicon native), Linux. Docker and Kubernetes support.
The local AI ecosystem has matured dramatically. In 2023, running a competent LLM locally required deep technical knowledge. In 2025, tools like Ollama, LM Studio, and LocalAI make it as simple as installing an app. Here is a comparison of the main options:
ollama run llama3. 180K+ GitHub stars.The most common question is "what hardware do I need?" Here is a practical guide:
For individual developers: install Ollama, run ollama run deepseek-coder:6.7b, and use VS Code with Continue extension for local code completion. For teams: deploy LocalAI behind your VPN with Docker Compose, set up Open WebUI as the front-end, and let everyone on the team use AI without data leaving your infrastructure.
Running models is only half the story. For researchers using local AI to process data, SciDraw provides AI-powered scientific figure generation that pairs well with local data analysis pipelines. For patent engineers working with confidential inventions locally, PatentFig offers AI-generated patent figures compliant with USPTO and CNIPA standards—keeping everything in a privacy-first workflow.
8 GB VRAM minimum for small models (3B–7B). 16 GB+ for larger models (13B–34B). Apple Silicon works via MLX without a discrete GPU.
Yes. Ollama and LM Studio have native macOS support for Apple Silicon (M1–M4). MLX provides Apple-optimized inference.
Ollama makes running LLMs locally as easy as Docker. One command downloads and runs models: ollama run llama3.
Yes. Open WebUI provides a full ChatGPT-style interface that connects to Ollama or any local OpenAI-compatible API.
Yes. DeepSeek-Coder, CodeLlama, and Qwen2.5-Coder all run locally. VS Code extensions like Continue connect to local models.
TopLocalAI is built for developers and teams who want to own their AI stack. We provide curated guides, hardware benchmarks, and setup walkthroughs so you can go from zero to running models locally in minutes.
Whether you need local LLMs for coding, vision models for document processing, or embeddings for RAG, TopLocalAI helps you choose and deploy the right tools on your hardware.