Overview
Description
Candle lets you deploy machine learning models in production without the bloat of Python frameworks — cutting server costs and startup times. You can run LLMs, image generators, and speech recognition on CPU or GPU with a small Rust binary. It is built for serverless inference, so you get fast scaling and lower infrastructure overhead.
Technical scorecard
License
Apache-2.0
Commercial use
Yes
OpenAI-compatible API
No
REST API
No
Fine-tuning support
Yes
Quantization support
Yes
Docker available
Yes
GUI / no-code available
No
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: Jul 22, 2026. Maintainer verification should be treated as directory guidance, not legal advice.
Deploying Candle in production?
Stop silent telemetry leaks before they trigger an unintended data leak. Get our Airgap Certainty Blueprint for Candle.
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/huggingface/candleHardware Requirements
Works Well With