Overview
Description
The big picture: llmfit turns the guessing game of "will this model run on my machine?" into a single command. It inspects your CPU cores, system RAM, GPUs, VRAM, and unified-memory setup, then ranks hundreds of open-source models by fit, speed, quality, and context. Here's why it matters: you don't waste hours downloading a 70B quant that will never fit, and you don't settle for a tiny model when your hardware could handle better. The bottom line: the right model, at the right quantization, for your exact hardware — entirely locally, with nothing sent anywhere unless you ask it to.
Technical scorecard
License
MIT
Commercial use
Yes
OpenAI-compatible API
No
REST API
Yes
Fine-tuning support
No
Quantization support
GGUF, AWQ, GPTQ, EXL2
Docker available
Yes
GUI / no-code available
Yes
Telemetry
Unknown
Offline after setup
Yes
Data & Privacy
Does it send data online?
After setup, this listing is marked as usable offline. Confirm network behavior against the upstream project before regulated deployment.
Does it store history?
Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.
License checks?
Commercial use is marked as allowed or likely allowed by the listed license.
Telemetry?
Unknown
Last verified: Sep 9, 2026. Maintainer verification should be treated as directory guidance, not legal advice.
Deploying llmfit in production?
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Request Privacy and Telemetry AuditSetup & Installation
A developer can usually get this running with standard docs.
# Start with the official project repository
# https://github.com/AlexsJones/llmfitHardware Requirements
Works Well With