Compare Portkey and Promptfoo side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
Choose Portkey if enterprise-scale monitoring (10B requests/month).
Choose Promptfoo if completely free and open source (MIT license).
Want to compare Portkey and Promptfoo 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.
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Website | portkey.ai | promptfoo.dev |
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.
Promptfoo is an open-source tool for testing prompts, agents, and RAGs, with AI red teaming, pentesting, and vulnerability scanning for LLMs. Built under MIT license, Promptfoo was originally developed for LLM apps serving over 10 million users in production. The platform compares performance across GPT, Claude, Gemini, Llama, and more with simple declarative configs supporting command line and CI/CD integration. The Community version includes up to 10,000 probes monthly at no charge, with infrastructure costs typically USD 50-500 monthly for hosting and LLM API calls. Developers praise Promptfoo for its speed, quality-of-life features like live reloads and caching, security features including red teaming, and budget-friendly open-source model. However, the CLI-focused approach creates friction for non-technical team members, and the platform lacks end-to-end observability, version control for prompts, and test management features needed for complex production agents.
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 →One platform for routing, observability, tracing, and evals across every LLM provider.