PRIVATE COMPUTE / LOCAL AI DIRECTORY
Build your own
AI workstation.
MaaLabs AI is a practical, offline-first handbook for running serious language models on your own Windows, Linux or macOS machine.
$ ollama list
NAME SIZE STATUS
qwen2.5-coder:32b 19.0 GB ready
devstral:24b 14.0 GB ready
deepseek-r1:32b 19.0 GB ready
$ ollama run qwen2.5-coder:32b_
THE LOCAL STACK
Everything you need
to stay in control.
Discover a model, size a machine, install a runtime and connect your tools. Every route points back to local execution.
Model atlas
Compare the approved 15-model shortlist and expanded directory by tier, domain, context and local status.
Open directory ↗02Hardware planner
Map RAM, GPU VRAM, CPU, storage, PSU and expected quality to a realistic local build.
Plan a build ↗03Local workflows
Use Claude-style local configuration patterns, Codex, Continue, Cline, Aider and Open WebUI without a cloud dependency.
See workflows ↗HOW IT WORKS
From download
to daily driver.
Choose
Start with a verified tag or a GGUF release that matches your hardware.
Run
Install Ollama, llama.cpp or MLX locally and validate the first response.
Connect
Add tools, project rules and local files only after the base model is stable.
Measure
Watch speed, memory, quality and context instead of chasing leaderboard numbers.
MADE FOR DEVELOPERS
Local AI that fits
your actual desk.
Whether you have 16 GB or 128 GB of RAM, the planner tells you what is sensible, what needs offload and where quality will drop.