Neptune vs Guild AI
Neptune
Guild AI
Commercial Requirements
Standalone component
Stand-alone open-source platform
Managed cloud service
Open-source
Free
General Capabilities
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
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
No
No
No
No
No
Experiment Tracking
No
No
No
No
No
No
No
NA
No
NA
No
NA
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Model Registry
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Integrations and Support
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
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Report outdated information here.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(key="DET")
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
Don’t overthink it