Weights & Biases
An integrated platform for developing, tracking, and managing machine learning models across experimentation, evaluation, and production deployment
- Also known as
- weights-biases
What is Weights & Biases?
A collaborative development platform that enables tracking of ML experiments, versioning of models, evaluation of AI systems, and deployment to production. It provides specialized observability and tracing capabilities for LLM applications, with support for both managed cloud and self-hosted infrastructure.
Weights & Biases pricing
We don't have Weights & Biases's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
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.
- Tool role
- End-to-end ML platform
- Self-hostable / OSS core
- ✓
- Managed cloud available
- ✓
- On-prem / VPC deployment
- ✓
- LLM tracing / observability
- ✓
- Evaluation (offline / LLM-judge / human)
- ✓
- Prompt management + versioning
- ✓
- Experiment tracking / model registry
- ✓
- Model serving / inference endpoint
- ✓
- OpenTelemetry / OpenLLMetry compatible
- -
- Framework-agnostic
- ✓
- Multi-provider model support
- ✓
- No-train-on-customer-data guarantee
- -
Platform & deployment
Independently observed- CLI
- iOS
- Web
- Cloud / SaaS
- On-premise
- Self-hosted
Integrations (16)
Independently observed- AWS Bedrock
- SambaNova Cloud
- Claude Code
- Friendli
- OpenAI
- Alibaba Qwen
- Meta Llama
- Microsoft Phi
- Hangzhou DeepSeek
- Z.ai GLM
- MoonshotAI Kimi
- CoreWeave
- LangChain
- TensorBoard•
- Google Agent Development Kit
- deepset
Security & compliance
Independently observed- ISO/IEC 27001:2022active
- ISO/IEC 27017:2015active
- ISO/IEC 27018:2019active
- SOC 2active
- HIPAAactive
- NIST 800-53active
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.
- LangChainAn open platform for building and managing AI agentsmedium · 69%
- PortkeyUnified command center for operating AI systems reliably in productionmedium · 74%
- BasetenAn inference platform for deploying AI models to production with high performance and global scalemedium · 72%
- Together AIOpen-source model hosting and inference platformmedium · 59%
- Ollamamedium · 56%
- RayDistributed computing framework for scaling machine learning and Python applicationsmedium · 65%
Compare Weights & Biases
Side by side against other mlops & llmops tools, attribute by attribute, with a source on every value.
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.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 100 | 0.07 | 7.0 | ✓ |
| Development activity | 63 | 0.09 | 5.9 | ✓ |
| Security posture | 85 | 0.06 | 5.4 | ✓ |
| Release cadence | 91 | 0.05 | 4.7 | ✓ |
| Dependent projects | 66 | 0.06 | 4.2 | ✓ |
| Integrations | 29 | 0.08 | 2.3 | ✓ |
| Stars | 76 | 0.03 | 2.0 | ✓ |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Security score | 0 | 0.04 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
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
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-10-05 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 6 items | mediumsource · 2026-09-10 · 66% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Role: platform · Evaluation: Yes · Managed cloud: Yes · Model serving: Yes · Self hostable: Yes · Multi provider: Yes | mediumsource · 2026-10-05 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 9 | mediumsource · 2026-10-05 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-10-05 · 90% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | MIT | highsource · 2026-10-05 · 95% |
Pricing
Release
Reliability
| Attribute | Value | Evidence |
|---|---|---|
| Status page | Yes | mediumsource · 2026-08-01 · 60% |
Security
| Attribute | Value | Evidence |
|---|---|---|
| Iso27001 | Yes | mediumsource · 2026-10-05 · 60% |
| Soc2 | Yes | mediumsource · 2026-10-05 · 60% |
| Disclosure policy | Yes | mediumsource · 2026-08-01 · 60% |
| Gdpr | Yes | mediumsource · 2026-10-05 · 60% |
| Hipaa | Yes | mediumsource · 2026-10-05 · 60% |
| Vulnerabilities | Count: 1 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=wandb&per_page=100 · Last 12m: 0 · Max severity: HIGH | highsource · 2026-10-05 · 90% |
| Certifications | ISO/IEC 27001:2022, ISO/IEC 27017:2015, ISO/IEC 27018:2019, SOC 2, HIPAA, NIST 800-53 | mediumsource · 2026-10-05 · 60% |
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