Braintrust vs Portkey
Detailed side-by-side comparison to help you choose the right tool
Braintrust
🔴DeveloperLLM Observability
AI observability platform for evals, production tracing, prompt management, and regression detection.
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Starting Price
FreePortkey
🔴DeveloperLLM Gateways & Infrastructure
AI gateway and control plane for production GenAI: routes calls across 250+ LLMs with one unified API, plus guardrails, prompt management, observability, budgets, and an MCP-aware agent runtime.
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Starting Price
CustomFeature Comparison
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Braintrust - Pros & Cons
Pros
- ✓Evals, tracing, and prompt playground in a single shared workbench
- ✓Playground pulls real production traces in for side-by-side comparison
- ✓Regression detection across model swaps is a first-class workflow
- ✓Native integrations with the major SDKs (OpenAI, Anthropic, LangChain, Vercel AI)
- ✓MCP support makes tool traces structured spans rather than blobs
Cons
- ✗Jump from Free to $249/mo Pro is steep with limited middle tier
- ✗LLM-as-judge scorers require careful rubric design to be reliable
- ✗Opinionated workflow — friction if your team prefers fully custom pipelines
- ✗Self-host only on Enterprise
Portkey - Pros & Cons
Pros
- ✓Provider-agnostic routing with declarative configs that an SRE can change without app deploys
- ✓Strong governance primitives (virtual keys, budgets, RBAC) that internal gateways usually skip
- ✓Built-in guardrails and observability remove the need for a separate vendor for each
- ✓Self-hosted and BYOC options make it viable for regulated and air-gapped deployments
Cons
- ✗Pricing page is JS-rendered and dollar amounts must be confirmed manually on site
- ✗Adds a network hop and latency overhead — small but non-zero next to direct provider calls
- ✗Overkill for single-provider single-app teams who do not need governance
- ✗Some advanced features (Agents, BYOC) require Enterprise contracts
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