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Quilt vs Weights & Biases

Quilt

6.1#24 in data version control toolsFrom $312.50 a month
WebAPILinuxSelf-hosted
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What both publish

FactQuiltWeights & Biases
AudienceQuilt describes its platform as built for life sciences teams, including computational biology and connected lab use cases.The maker presents the platform for AI developers and highlights use cases including model training, fine-tuning, AI application development, and production monitoring.
DeploymentQuilt deploys inside the customer's AWS VPC, with data remaining in their S3 buckets; the page says the only external connection is license validation.W&B offers multi-tenant SaaS, isolated dedicated cloud and customer-managed cloud or on-premises deployments.
IntegrationsThe integrations page describes bi-directional sync with Benchling and integrations with Nextflow and Ganymede for pipeline and instrument data.W&B is designed to integrate with customers' ML stacks and tools and offers managed or self-managed deployment choices.
SecurityQuilt lists SOC 2 Type II, HIPAA-eligible infrastructure, GxP-ready audit trails, and readiness for 21 CFR Part 11 workflows.The SaaS deployment states SOC 2 Type 2 certification, team-level data isolation and SSO support.
SupportThe pricing page lists Enterprise Support, Priority implementation support, and Premium Support on progressively higher plans.Support tiers are Standard, Standard Plus and Premium; Premium adds 24/7 coverage, faster response targets, roadmap sessions and engineering access.

Quilt plans

  • Enterprise+$312.50 a month
  • Enterprise Scale$425 a month
  • Enterprise$625 a month
  • Startup$750 a month

Weights & Biases plans

  • FreeFree
  • PersonalFree
  • Pro$60 a month
  • Advanced EnterprisePriced on request
  • EnterprisePriced on request

Pick Quilt if…

You want what its maker publishes above — check its page for the details.

Pick Weights & Biases if…

It suits AI developers working on model training, fine-tuning, AI applications, or production monitoring. The free tier may fit smaller projects, while larger teams should note the stated Pro-to-Enterprise transition guideline.

Charts they share