Helicone vs Braintrust
Detailed side-by-side comparison to help you choose the right tool
Helicone
🔴DeveloperLLM Observability
Open-source LLM observability and AI gateway — logs every prompt, response, cost, and latency across 20+ providers with a one-line proxy or async SDK, plus caching, retries, and prompt experiments.
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Starting Price
FreeBraintrust
🔴DeveloperLLM Observability
Braintrust is an evals-first LLM observability platform combining production tracing, prompt playgrounds, autoevals, and Topics-based pattern discovery for teams shipping AI in production.
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Starting Price
FreeFeature Comparison
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💡 Our Take
Choose Helicone for cost tracking and operational controls (caching, rate limiting) on production LLM traffic with minimal setup. Choose Braintrust if your primary need is rigorous LLM evaluation, prompt playgrounds, and experiment tracking with human-in-the-loop scoring. Braintrust is evaluation-first; Helicone is observability-first — they solve adjacent but different problems.
Helicone - Pros & Cons
Pros
- ✓5-minute proxy integration captures full traces, cost, and latency across 20+ providers
- ✓Real AI gateway features (caching, retries, fallback, key vault) replace a custom proxy
- ✓MIT-licensed and self-hostable on Postgres + ClickHouse — passes regulated procurement
Cons
- ✗Proxy mode adds a network hop unless self-hosted in your own region
- ✗Prompt experiment UX is less mature than dedicated eval platforms like Braintrust
- ✗Self-hosting requires running ClickHouse, which is an extra ops surface
Braintrust - Pros & Cons
Pros
- ✓Evals-first design with versioned datasets, side-by-side prompt comparisons, and autoevals library means iteration is the default workflow, not an afterthought
- ✓Brainstore (purpose-built for AI traces) and the official MCP server make large-scale log search and IDE-driven prompt iteration meaningfully faster than competitors
- ✓Generous Starter tier ($0/mo with 1 GB processed data, 10k scores, unlimited users/projects/datasets) lets teams ship real evals before paying anything
Cons
- ✗$249/month Pro tier is a steep first paid step versus self-hosting Langfuse, which is free if you run the open-source version on your own infrastructure
- ✗Topics token costs ($0.06/mtok input, $0.40/mtok output beyond credits) can spike quickly on chatty production traffic with custom facets
- ✗No built-in LLM gateway, prompt router, or model fallback layer — you still need OpenRouter or similar for routing and resilience
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