Portkey vs Vellum
Detailed side-by-side comparison to help you choose the right tool
Portkey
🔴DeveloperLLM Gateway & Observability
Production AI control plane: AI gateway, prompt management, observability, guardrails, and MCP gateway in front of 1,600+ LLM providers.
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Starting Price
FreeVellum
🔴DeveloperTesting & Quality
LLM development platform for prompt engineering, evaluation, workflow orchestration, and deployment of production AI applications. Helps engineering teams build, test, and ship LLM-powered features with version control and observability.
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FreeFeature Comparison
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💡 Our Take
Choose Vellum if you need prompt engineering, evaluation, and workflow orchestration in one platform. Choose Portkey if you primarily need an AI gateway with routing, caching, and observability across LLM providers. Vellum covers the development lifecycle; Portkey focuses on the inference layer.
Portkey - Pros & Cons
Pros
- ✓OpenAI-compatible API gives teams one integration point while still routing to 1,600+ models across providers such as OpenAI, Anthropic, Google, Mistral, AWS Bedrock, Azure OpenAI, Cohere, Together, Fireworks, and Groq.
- ✓Fallback and load-balancing are built into the gateway layer, so reliability policies can be configured centrally instead of duplicated across each application service.
- ✓Combines 5 production AI functions in one platform: AI gateway, prompt management, observability, guardrails, and MCP Gateway.
- ✓Prompt versioning and A/B testing help teams change production prompts with more control than hard-coded prompt strings in application code.
- ✓Observability includes per-request tracing and cost analytics, which is especially useful when several teams or products share model providers.
- ✓Enterprise options mentioned in the available content include VPC deployment, SSO, audit logs, and SOC 2 / HIPAA support.
Cons
- ✗Adds a hosted gateway hop between the application and the LLM provider, so teams must evaluate added latency and dependency risk.
- ✗The main paid self-serve plan is $49/month for 100k recorded logs, with overage fees beyond that included quota.
- ✗May be more platform than needed for teams that only want basic LLM request logging or tracing.
- ✗Advanced enterprise controls such as VPC deployment, SSO, audit logs, and compliance support appear oriented toward Enterprise contracts rather than small self-serve users.
- ✗Teams must learn Portkey-specific routing, guardrail, prompt, and gateway configuration concepts before they get full value.
Vellum - Pros & Cons
Pros
- ✓Complete LLM development lifecycle in one platform — from prompt engineering through production monitoring
- ✓Automated evaluation pipelines catch prompt regressions before they reach users
- ✓Visual workflow builder enables complex AI pipelines without orchestration code
- ✓Model-agnostic approach supports OpenAI, Anthropic, Google, and other providers side by side
- ✓SOC 2 Type II certified with HIPAA compliance available for regulated industries
- ✓Strong API and SDK support (Python, TypeScript) for CI/CD integration
Cons
- ✗Learning curve for teams new to structured LLM development practices
- ✗Pro tier at $89/seat/month is higher than some competitors, and Enterprise requires custom sales engagement
- ✗Adds a dependency layer between your application and LLM providers
- ✗Workflow builder may be less flexible than code-first orchestration for very complex pipelines
- ✗Evaluation framework effectiveness depends on teams defining good test criteria
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