Portkey vs Weights & Biases: Observability, Prompts & Evals Comparison
Compare Portkey and Weights & Biases side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose Portkey if enterprise-scale monitoring (10B requests/month).
Choose Weights & Biases if free tier for personal projects and academic research provides excellent value.
Want to compare Portkey and Weights & Biases on your own traffic?
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | — | Freemium |
| Best For | — | ML engineers and researchers who need comprehensive experiment tracking |
| Website | portkey.ai | wandb.ai |
| Key Features | — |
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| Use Cases | — |
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Pros & Cons: Portkey vs Weights & Biases
- +Enterprise-scale monitoring (10B requests/month)
- +Sub-40ms overhead
- +Comprehensive analytics and tracing
- +Strong security certifications
- −Professional tier expensive (USD 2-5k/mo)
- −Open-source has limited features
- −Complex for small teams
- +Free tier for personal projects and academic research provides excellent value
- +Comprehensive experiment tracking and model versioning capabilities
- +Strong visualization tools help teams understand model performance
- +Acquisition by CoreWeave provides infrastructure synergies and stability
- −Pricing can become expensive for large teams and enterprises
- −Additional storage costs can add up quickly for data-intensive workflows
- −Learning curve for advanced features may slow initial adoption
- −Platform complexity may be overkill for simple ML projects
Pricing: Portkey vs Weights & Biases
- · Open-source
- · Basic observability
- · Self-managed
- · Community support
- · Managed service
- · Advanced analytics
- · Standard support
- · Team features
- · Custom limits
- · SOC2, ISO27001
- · Priority support
- · Private deployment
- · Personal projects
- · Limited storage
- · Community support
- · Core features
- · Full product features
- · Enhanced storage
- · Email support
- · Team collaboration
- · For academic research
- · Unlimited tracked hours
- · 200GB cloud storage
- · Up to 100 seats
- · Custom pricing
- · Advanced features
- · Dedicated support
- · SLA guarantees
When to Choose Portkey vs Weights & Biases
- ML experiment tracking and comparison
- Model training run management
- Team collaboration on ML projects
About Portkey
Portkey Observability is the monitoring and analytics component of the Portkey AI platform, providing comprehensive visibility into LLM applications. The platform tracks requests, costs, latency, errors, and user behavior across all LLM providers. Portkey Observability integrates seamlessly with the Portkey AI Gateway, offering unified monitoring for multi-provider AI applications. The platform provides real-time dashboards, alerting, and detailed trace analysis to help teams optimize AI performance and costs. Portkey processes over 10 billion requests monthly with sub-40ms overhead, providing enterprise-grade observability for production AI systems.
About Weights & Biases
Weights and Biases (W and B) is a machine learning operations platform founded in 2017 by Chris Van Pelt, Lukas Biewald, and Shawn Lewis in San Francisco, California. The platform offers performance visualization tools for machine learning, helping companies track models, visualize performance, and automate training and model improvement workflows. W and B provides comprehensive experiment tracking, model versioning, and collaborative tools for ML teams. In March 2025, Weights and Biases was acquired by CoreWeave, strengthening its position in the AI infrastructure ecosystem. The company raised a total of USD 250M from investors including CoreWeave, Coatue, Bloomberg Beta, and Insight Partners. W and B offers a free tier for personal projects and provides academic institutions with free Pro licenses for non-profit research, including unlimited tracked hours, 200GB cloud storage, up to 25GB/month of Weave data ingestion, and up to 100 seats. Paid plans start at USD 60/month with additional cloud storage available at USD 0.03 per GB.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evalstools →Other Observability, Prompts & Evals Tools
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