Neptune vs Guild AI


Neptune

Guild AI
Commercial Requirements
Standalone component

Stand-alone open-source platform

Can be deployed both on-premises and/or on the cloud, but has to be self-managed
Managed cloud service

Open-source
General Capabilities
No special requirements other than having the neptune-client installed and access to the internet if using managed hosting. Check here for infrastructure requirements for on-prem deployment.

Guild.ai needs only Python and pip installed
Minimal. Just a few lines of code needed for tracking. Read more

No code change required for basic tracking
Yes, through the neptune-client library

Yes, through their CLI and Python API
No

Yes

No

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No

No
Experiment Tracking




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NA
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NA

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Model Registry
No

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Integrations and Support
No

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No
Report outdated information here.
What are the key advantages of Neptune then?

- Comparison features (including notebooks or image comparison, and more)
- 25+ out-of-the box integrations with Python libraries and IDEs
- Scalability with thousands of runs
- User management and team collaboration feature
See these features in action
Sign up to Neptune and install client library
pip install neptune
Track experiments
import neptune
run = neptune.init_run()
run["params"] = {
"lr": 0.1, "dropout": 0.4
}
run["test_accuracy"] = 0.84
Register models
import neptune
model = neptune.init_model()
model["model"] = {
"size_limit": 50.0,
"size_units": "MB",
}
model["model/signature"].upload(
"model_signature.json")
Thousands of ML people already chose their tool
It only takes 5 minutes to integrate Neptune with your code
Donât overthink it