Braintrust vs Promptfoo: Observability, Prompts & Evals Comparison
Compare Braintrust and Promptfoo side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose Braintrust if custom-built Brainstore database optimized for AI data with fast full-text search and low latency.
Choose Promptfoo if completely free and open source (MIT license).
Want to compare Braintrust 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.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Freemium | — |
| Best For | AI teams who need a unified platform for logging, evaluating, and improving LLM applications | — |
| Website | braintrust.dev | promptfoo.dev |
| Key Features |
| — |
| Use Cases |
| — |
Pros & Cons: Braintrust vs Promptfoo
- +Custom-built Brainstore database optimized for AI data with fast full-text search and low latency
- +Framework agnostic with native SDKs for multiple languages and no vendor lock-in
- +Comprehensive security and compliance certifications including SOC 2 Type II, GDPR, and HIPAA
- +AI-assisted Loop Agent for automated optimization of prompts and evaluations
- +Strong backing with $80M Series B funding and customers including Vercel, Notion, Coursera, and Dropbox
- −Relatively new platform founded in 2022, less mature than some competitors
- −Pro plan at $249/month may be expensive for smaller teams or individual developers
- −Limited public information about advanced features and customization options
- +Completely free and open source (MIT license)
- +Fast with quality features like live reloads and caching
- +Built-in red teaming and security vulnerability scanning
- +Trusted by large companies with strong community
- −CLI-focused creates friction for non-technical users
- −Limited observability for complex production agents
- −No version control for prompts, data, or metrics
- −Offline nature hits ceiling for production scale
Pricing: Braintrust vs Promptfoo
- · MIT license
- · Up to 10k probes/month
- · All core features
- · CLI and browser UI
- · Hosting costs
- · Database expenses
- · LLM API calls
- · Variable by usage
- · Advanced features
- · Higher probe limits
- · Priority support
- · Custom security
When to Choose Braintrust vs Promptfoo
- Iterating on prompts with real production data
- Running evaluations across model versions
- Building golden datasets from production traffic
About Braintrust
Braintrust is an AI observability and evaluation platform that helps teams build, monitor, and improve AI applications in production. The platform enables users to turn production traces into evaluations, compare prompts and models, and improve quality with every release. Built on a custom database called Brainstore designed specifically for AI data complexity, Braintrust provides real-time trace inspection, performance monitoring for latency, cost, and quality, along with automated alerts. The platform features Loop Agent for AI-assisted optimization of prompts, scorers, and datasets, and offers framework-agnostic native SDKs for Python, TypeScript, Go, Ruby, and C# with no vendor lock-in. Braintrust is SOC 2 Type II, GDPR, and HIPAA compliant with SSO/SAML integration and granular role-based access control.
About Promptfoo
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.
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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