vioscaleAI
Comparison

Ray vs Weights & Biases

On the evidence we track, Ray leads this comparison with a composite score of 71/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.

Ray full profile →Weights & Biases full profile →
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★Ray71
Weights & Biases65
Score
vioscaleAI score
Ray71 / 100medium · 65%
Weights & Biases65 / 100low · 44%
Pricing
Free tier
Ray✓
Weights & Biases✓
Model
Raycommercial
Weights & Biasesfree
Price level
Rayfree
Weights & Biasesfree
Transparent
Ray–
Weights & Biases✗
Integrations
Count
Ray17
Weights & Biases9
Security
Certifications
Disclosure policy
Ray–
Weights & Biases✓
Gdpr
Ray–
Weights & Biases✓
Hipaa
Ray–
Weights & Biases✓
Iso27001
Ray–
Weights & Biases✓
Scorecard
Ray5.7
Weights & Biases–
Soc2
Ray–
Weights & Biases✓
Vulnerabilities
Reliability
Status page
Ray✓
Weights & Biases✓
Adoption
Dependent repos
Ray3,641
Weights & Biases9,299
Github stars
Ray44,036
Weights & Biases11,268
Package downloads weekly
Ray11,291,327
Weights & Biases–
Activity
Commits last 30d
Ray100
Weights & Biases100
Release
Cadence days
Ray18
Weights & Biases16
History
Ray20 items
Weights & Biases20 items
License
Spdx
RayApache-2.0
Weights & BiasesMIT
Language
Primary
RayPython
Weights & BiasesPython
Content
Faq
Ray6 items
Weights & Biases6 items

Capabilities

Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.

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

What each one is

The product in its own terms, so the numbers below have context.

Ray

Leader

Open-source framework for building and scaling distributed ML and Python applications, supporting the full pipeline from data processing and model training to inference and serving with simple APIs.

Independently observed

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.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Ray

Leader
Open source
as of verify ↗

Weights & Biases

FreeFree tier
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
Ray✗
Weights & Biases✓
iOS
Ray✗
Weights & Biases✓
CLI
Ray✓
Weights & Biases✓
Deployment
Cloud / SaaS
Ray✓
Weights & Biases✓
Self-hosted
Ray✓
Weights & Biases✓
On-premise
Ray✗
Weights & Biases✓

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

Ray

Leader
27 total
  • PyTorch
  • TensorFlow
  • AIBrix
  • AReaL
  • Cosmos Curate
  • Daft
  • Data-Juicer
  • DeltaCAT
  • Modin
  • NeMo Curator
  • NeMo-RL
  • OpenRLHF
  • RayDP
  • ROLL
  • SkyRL
  • SLIME
  • Syftr
  • verl
  • vLLM
  • Kubernetes
  • AWS
  • GCP
  • Azure
  • Databricks
  • +3 more
Independently observed

Weights & Biases

16 total
  • OpenAI
  • Alibaba Qwen
  • Meta Llama
  • Microsoft Phi
  • Hangzhou DeepSeek
  • Z.ai GLM
  • MoonshotAI Kimi
  • CoreWeave
  • LangChain
  • TensorBoard
  • AWS Bedrock
  • Claude Code
  • Google Agent Development Kit
  • SambaNova Cloud
  • Friendli
  • deepset
Independently observed
Still deciding?

Ray or Weights & Biases: which one depends on you

A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.

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

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.