Weights & Biases

Platform for tracking AI experiments and managing model development

Also known as
weights-biases

What is Weights & Biases?

Weights & Biases provides an AI development platform for building and managing machine learning models with integrated experiment tracking, dataset and model management, prompt versioning, and collaborative code features. It supports multiple deployment options including cloud-hosted SaaS, dedicated instances, and self-managed deployments.

Independently observed

What Weights & Biases does

The capabilities that matter for mlops & llmops tools, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.

Core
Tool role
End-to-end ML platform
Deployment
Self-hostable / OSS core
Managed cloud available
On-prem / VPC deployment
Observability
LLM tracing / observability
Evaluation (offline / LLM-judge / human)
Dev
Prompt management + versioning
Tracking
Experiment tracking / model registry
Serving
Model serving / inference endpoint
Interop
OpenTelemetry / OpenLLMetry compatible
-
Framework-agnostic
Gateway
Multi-provider model support
-
Data
No-train-on-customer-data guarantee
-
Independently observed

Platform & deployment

Independently observed
Platforms
  • iOS
  • Web
Deployment
  • Cloud / SaaS
  • Self-hosted

Integrations (10)

Independently observed
  • OpenAI
  • Alibaba Qwen
  • Meta Llama
  • Microsoft Phi
  • Hangzhou DeepSeek
  • Z.ai GLM
  • MoonshotAI Kimi
  • CoreWeave
  • LangChain
  • TensorBoard

Security & compliance

Independently observed
  • ISO/IEC 27001:2022active
  • ISO/IEC 27017:2015active
  • ISO/IEC 27018:2019active

Known vulnerabilities: 1 (0 in the last 12 months), max severity HIGH sourcea count reflects scale & disclosure, not quality

Weights & Biases FAQ

Common questions about Weights & Biases, answered from independent, dated evidence.

What is Weights & Biases?

Weights & Biases provides an AI development platform for building and managing machine learning models with integrated experiment tracking, dataset and model management, prompt versioning, and collaborative code features. It supports multiple deployment options including cloud-hosted SaaS, dedicated instances, and self-managed deployments. It is indexed under MLOps & LLMOps Tools.

Source: https://wandb.ai

What platforms does Weights & Biases support?

Weights & Biases supports the web and iOS. Platforms we have not confirmed are simply not listed here rather than ruled out.

Source: https://wandb.ai

Can Weights & Biases be self-hosted?

Yes. Weights & Biases can be deployed cloud / SaaS and self-hosted, so it does not have to run on the vendor's infrastructure.

Source: https://wandb.ai

What does Weights & Biases integrate with?

We have confirmed 10 integrations for Weights & Biases, including OpenAI, Alibaba Qwen, Meta Llama, Microsoft Phi, Hangzhou DeepSeek, Z.ai GLM, MoonshotAI Kimi and CoreWeave, plus 2 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.

Source: https://wandb.ai

What security certifications does Weights & Biases have?

We have independently confirmed SOC 2, ISO 27001, HIPAA and GDPR for Weights & Biases. Certifications we do not list are ones we have not been able to verify from public sources, which is not the same as Weights & Biases not holding them. Always confirm compliance directly before you rely on it.

Source: https://wandb.ai

Is Weights & Biases open source?

Yes. Weights & Biases is published under the MIT licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.

Source: https://github.com/wandb/wandb

Weights & Biases alternatives

Other mlops & llmops tools we track, ranked by the same independent score.

All Weights & Biases alternatives, ranked →

Compare Weights & Biases

Side by side against other mlops & llmops tools, attribute by attribute, with a source on every value.

Independent · unbought · dated

The vioscaleAI score: one lens on the evidence

Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Weights & Biases, not the verdict.

Balanced composite 63 / 100
low · 44%
Signal contributions to the composite score
SignalScoreWeightContributionEvidence
Capabilities960.076.8
Development activity630.095.9
Security posture850.065.4
Release cadence910.054.7
Dependent projects660.064.2
Stars760.032.0
Integrations200.081.6
Package downloads00.140.0-
Security score00.040.0-
Developer Q&A activity00.060.0-

Computed . Re-weight it by intent, or see the full method.

All data & sourcesshow ↓

Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.

Activity

AttributeValueEvidence
Commits last 30d100mediumsource · 2026-09-07 · 65%

Adoption

AttributeValueEvidence
Github stars11,246highsource · 2026-09-07 · 90%
Dependent repos9,299highsource · 2026-09-07 · 85%

Content

AttributeValueEvidence
Faq6 itemsmediumsource · 2026-09-10 · 66%

Features

AttributeValueEvidence
CapabilitiesRole: platform · Evaluation: Yes · Managed cloud: Yes · Model serving: Yes · Self hostable: Yes · Vpc deployment: Yesmediumsource · 2026-09-07 · 60%

Integrations

AttributeValueEvidence
Count4mediumsource · 2026-09-07 · 60%

Language

AttributeValueEvidence
PrimaryPythonhighsource · 2026-09-07 · 90%

License

AttributeValueEvidence
SpdxMIThighsource · 2026-09-07 · 95%

Pricing

AttributeValueEvidence
Modelcommerciallowsource · 2026-09-07 · 40%

Release

AttributeValueEvidence
Cadence days16mediumsource · 2026-09-07 · 70%
History20 itemsmediumsource · 2026-09-07 · 70%

Reliability

AttributeValueEvidence
Status pageYesmediumsource · 2026-08-01 · 60%

Security

AttributeValueEvidence
Iso27001Yesmediumsource · 2026-09-07 · 60%
Soc2Yesmediumsource · 2026-09-07 · 60%
Disclosure policyYesmediumsource · 2026-08-01 · 60%
GdprYesmediumsource · 2026-09-07 · 60%
HipaaYesmediumsource · 2026-09-07 · 60%
VulnerabilitiesCount: 1 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=wandb&per_page=100 · Last 12m: 0 · Max severity: HIGHhighsource · 2026-09-07 · 90%
CertificationsISO/IEC 27001:2022, ISO/IEC 27017:2015, ISO/IEC 27018:2019mediumsource · 2026-09-07 · 60%
Still deciding?

Is Weights & Biases the right choice for you?

Tell us the job, the constraints and what you weigh most, and we will rank Weights & Biases against the rest of the mlops & llmops tools we index, using the same dated evidence weighted your way.

Free to run, no account needed to start. How the evaluation works

For the makers of Weights & Biases

Is this your product?

This profile was built from public sources without asking you. You can take the badge below and use it anywhere, and you can claim the profile to correct anything we got wrong. Both are free, and neither moves Weights & Biases up or down: nobody can buy rank here, including you.

Take the badge

Live, always current, and free to use on your own site. It shows Weights & Biases's independent score and links back to this profile.

Weights & Biases, verified on vioscaleAI
HTML
<a href="https://www.vioscale.ai/software/weights-biases" target="_blank" rel="noopener">
  <img src="https://www.vioscale.ai/badge/software/weights-biases.svg" alt="Weights & Biases, verified on vioscaleAI" width="330" height="76" loading="lazy" />
</a>
Markdown, for a README →
Markdown
[![Weights & Biases, verified on vioscaleAI](https://www.vioscale.ai/badge/software/weights-biases.svg)](https://www.vioscale.ai/software/weights-biases)

Claim the profile

Verify you control the domain and you can correct the facts, add the sources we should be reading, and see how AI assistants are describing Weights & Biases. Free, and it does not change the score.

  • Correct anything wrong, with evidence
  • Point our crawler at the pages that matter
  • See which AI systems are reading this profile
Claim Weights & Biases

Not the owner? How vendor profiles work