Compare Neptune vs Weights & Biases

Keep the features you rely on and gain a snappier UI

vs

Weights & Biases

Log thousands of internal model metrics you need for debugging and actually be able to use them.
Browse, visualize, and compare your results in seconds. Whether in the cloud or self-hosted.

Contact us Show me feature-by-feature comparison

See how fast Neptune renders metrics in a large sample project

Responsive UI at scale

Navigate & visualize thousands of metrics in minutes milliseconds

Neptune doesn’t rely only on the browser to visualize your logs. Instead, it preprocesses your data at ingestion in a powerful backend. So, even if you track massive amounts of per-layer metrics, you can quickly search, filter, and display them to monitor results. No stalled queries. No stuck charts.

Just wanted to say, I LOVE Neptune. It’s actually fast!

Research Scientist Top Reasearch Lab working on SOTA LLMs

Self-hosted deployment

Deploy on-prem or in your private cloud. From day one.

The sensitivity of your research makes deployment on your own infra essential. You shouldn’t be forced into a cloud-only option. With Neptune, you can get a secure and scalable self-hosted version adapted to the size of your project and your volume of logs.

You get high availability, horizontal scalability, and everything inside your network by design. Plus, our engineering team provides clear guidance and support to ensure a seamless and quick rollout.

For us, self-hosted deployment was too difficult and time-consuming in the previous solution. We could achieve that with Neptune, and it allowed us to close important deals that had stringent security requirements.

Daniel Danciu CTO at Cradle Bio

Switching to Neptune is simpler than you think

WandB and Neptune’s client libraries are similar enough that you can migrate without worrying that anything will break along the way.

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Check the script

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See WandB to Neptune methods mapping

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Feature-by-feature comparison

All the tracking tools you need, built to handle scale

Compare experiment tracking, model monitoring, and debugging features to check if you can move from WandB to Neptune without losing core capabilities.

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Neptune

Weights & Biases

Commercial offering

Commercial offering

Open-source software or a managed cloud service?

Managed cloud service

Managed cloud service

Pricing model

User based and usage based (ingestion data points)

User based and usage based (tracked hours)

Guarantees around service levels (SLOs / SLAs)

Support 24×7

User access management (SSO, ACL)

Security policy and compliance

General information

Deployment

Cloud (SaaS)

Yes

Yes

Self-hosted (on-prem, private cloud)

Installation in air-gapped environment

Yes

Yes

Setup

Infrastructure requirements

Minimal setup—install the Python client and ensure internet access (for managed hosting). Self-hosting requires additional infrastructure; see requirements here.

Minimal setup—install wandb python library and ensure internet access (for managed hosting). Self-hosting requires additional infrastructure; see requirements here.

Integration with the training process

A few lines of code via the Neptune Python library.

A few lines of code via Python, JavaScript, or CLI.

Flexibility and accessibility

Accessing model metadata

CLI/custom API and Python SDK

CLI/custom API, Python SDK, Java SDK, Julia SDK

Supported operations

Search, Update, Delete, Download

Search, Update, Delete, Download

Logging modes

Offline, Disabled/Off, Asynchronous

Offline, Disabled/off, Asynchronous, Synchronous

Customizable metadata structure

Distributed training support

Pipelining support

Yes

Live monitoring

Yes

Yes

Webhooks and notifications

No

Resuming experiments

Forking runs

Capabilities

Log and display

Parameters

Single values (metrics, losses, gradients, activations, etc.)

Series of values (metrics, losses, gradients, activations, etc.)

Series aggregates (min/max/avg/var/last)

Yes

Tags

Descriptions/comments

Rich format

Images, Plots, Video, Audio

Images, Plots, Interactive visualizations, Video, Audio

Hardware consumption

CPU, GPU, TPU, Memory

Dataset

No

Code versions

Git, Source, Notebooks

System information

Console logs, Execution command

Console logs, Error stack trace, Execution command, System details

Environment config

No

pip requirements.txt, Docker Dockerfile

Files (model binaries, CSV)

External file reference (S3 buckets)

No

Searching & filtering

Searching on multiple criteria

Query language and filtering options

Both regex and fixed selectors

Regex on names at the project level, fixed selectors at the run level

Custom attribute filtering (e.g. tags)

Yes

Support for regular expressions

Auto-update charts based on regex

Yes

Saving searches and filter history

Visualizations

Custom (calculated) metrics

Forked charts

Histograms

Custom axes

Yes

Customizable global settings

Customizable legends

Comparing experiments

Table format diff

Single-metric overlayed plots

Multi-metric overlayed plots

Grouping experiments by metadata

Scatter plot

Parallel coordinates plot

No

Parameter importance plot

No

Rich format (side by side)

No

Images, Audio, Video, Interactive visualizations, Text

Data versions diff

No

No

Cross-project comparisons

Custom analysis

Experiment table customization

Saving experiment table views

Dashboards combining different metadata types

Custom widgets and plugins

No

Persistent custom plots coloring

Yes

Collaboration and knowledge sharing

Reports

Adding text in Reports

Commenting

Downloading charts

Yes

Sharing persistent UI links

Yes

User groups and ACL

This table was updated on 14 May 2025. Some information may be outdated.
Report outdated information here.

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