Tooling

Self-Hosted AI & LLMs

Ollama, Open WebUI, LocalAI, vLLM — run models on your own hardware.

Local model runners

Chat UIs (front-ends)

Code assistants (local Copilot)

Image generation

Speech (STT / TTS)

  • See Transcription — whisper.cpp, Faster Whisper, Vosk, Piper TTS, F5-TTS.

Voice / agent / autonomous

Vector / RAG

Patterns to adopt

  • Ollama + Open WebUI is the canonical "I want a chat UI on my GPU box" combo.
  • Pull models you'll actually use, not 50. Disk fills fast.
  • Pin model versions (llama3:8b-instruct-q4_K_M vs. llama3 tag).
  • GPU passthrough matters — Docker + NVIDIA / AMD container toolkit.
  • Mac Studios are remarkable inference boxes for the size; M-series unified memory loads larger models than equivalent NVIDIA cards.
  • Quantization — q4 / q5 quantized models run on consumer GPUs without quality cliff for chat.
  • Cache embeddings — re-computing on every query is wasteful.

Pick this if…

  • Default home / small team: Ollama + Open WebUI.
  • Production OpenAI-compatible API: vLLM or LocalAI.
  • Multi-provider chat UI: LibreChat.
  • Documents-with-chat all-in-one: AnythingLLM.
  • Local code Copilot: Continue.dev or TabbyML.
  • Image gen: ComfyUI (power user) or Fooocus (simpler).
  • Mac: MLX-LM + a UI like Hollama or Jan.

On this page