Local LLM tooling for developers
Running models locally is no longer a hobby-only path. This guide maps the local stack db.fyi tracks so you can choose runtimes, UIs, and serving layers without guessing.
Start here
| Need | Start with | Hub / task |
|---|---|---|
| Chat + pull models fast | Ollama | Local AI tools |
| Desktop app UX | LM Studio, GPT4All | |
| Max performance on CPU/GPU | llama.cpp | AI for local LLMs |
| Production-ish throughput | vLLM, TGI | AI for serving LLMs |
| IDE with local models | Continue, Tabby | Best AI coding assistants |
Decision rules
- If you want the least friction, start with Ollama + Open WebUI / Continue.
- If you care about raw llama.cpp features, use llama.cpp or LM Studio (which packages it).
- If you are serving many concurrent users, prefer vLLM / TGI / SGLang—not a desktop chat app.
- If coding agents need tools, pair a local runtime with an agent that supports local endpoints (Goose, Aider, Continue).
Compare pages
Related tasks
What we will not claim
Local does not automatically mean private or secure. Verify data paths, telemetry, and license terms on each product page.