Galileo AI vs Portkey: Observability, Prompts & Evals Comparison
Compare Galileo AI and Portkey side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose Galileo AI if generous free tier with 5,000 traces/month including Agent Reliability Platform.
Choose Portkey if enterprise-scale monitoring (10B requests/month).
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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 | AI teams who need to measure and improve the quality of their LLM outputs | — |
| Website | rungalileo.io | portkey.ai |
| Key Features |
| — |
| Use Cases |
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Pros & Cons: Galileo AI vs Portkey
- +Generous free tier with 5,000 traces/month including Agent Reliability Platform
- +Recognized as Gartner Cool Vendor demonstrating industry validation
- +Research-backed metrics providing scientific rigor to evaluations
- +Real-time observability with automated drift detection and alerting
- +Established team of 142 employees providing solid support capacity
- −Limited public information about advanced features and capabilities
- −Pro plan pricing jumps from free to $100/month with potential gaps for small teams
- −Less community-driven compared to open-source alternatives like Langfuse
- +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
Pricing: Galileo AI vs Portkey
- · Open-source
- · Basic observability
- · Self-managed
- · Community support
- · Managed service
- · Advanced analytics
- · Standard support
- · Team features
- · Custom limits
- · SOC2, ISO27001
- · Priority support
- · Private deployment
When to Choose Galileo AI vs Portkey
- Monitoring LLM output quality
- Detecting and preventing hallucinations
- Evaluating RAG pipeline accuracy
About Galileo AI
Galileo is an AI observability and evaluation platform designed to provide AI reliability for teams across the entire development lifecycle. The platform offers real-time observability that continuously evaluates systems in production, sending alerts if something goes wrong or if interactions drift from training data. Galileo provides powerful, research-backed metrics and evaluation-powered development workflows to help teams build, scale, monitor, and protect AI applications in real-time. The platform is recognized as a Gartner Cool Vendor and serves as a comprehensive solution for AI teams looking to ensure reliability and performance of their LLM applications. With the Agent Reliability Platform available as part of their free tier, Galileo makes advanced AI observability accessible to teams of all sizes. The platform emphasizes scalability, security, and premium support for enterprise customers while maintaining an approachable entry point through their generous free tier.
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.
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.
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