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BerriAI/litellm vs Kong/kong

Compare BerriAI/litellm and Kong/kong using the current verified snapshot: positioning, license, deployment, use cases, limitations, and original sources.

BerriAI/litellm

LiteLLM is an open-source AI gateway and Python SDK that provides a single OpenAI-format interface to over 100 LLM providers. It centralizes routing, cost tracking, virtual keys, and guardrails, making it useful for enterprise teams and developers managing multiple external or self-hosted models.

License
License pending
Deployment
Python environment
Use cases
Enterprise teams, developers, and AI engineers who need to standardize API calls, manage costs, and apply consistent routing rules across multiple external LLM providers. · Teams requiring an admin dashboard and virtual keys to manage multi-tenant LLM usage.
Updated
2026-07-17T06:30:35Z

Original project link

Kong/kong

Kong is a cloud-native gateway that proxies and governs conventional API traffic, microservices, and agentic LLM and MCP traffic. It provides a platform-agnostic proxy layer with plugin extensibility, declarative deployment modes, and traffic governance for AI and MCP integrations.

License
Apache-2.0
Deployment
Refer to project documentation
Use cases
Developers and operations teams who need a platform-agnostic proxy layer to centralize functionality and governance across microservices, conventional APIs, and agentic LLM and MCP traffic. · Teams seeking deployment flexibility for their API infrastructure using declarative databaseless or hybrid control-plane and data-plane models.
Updated

Original project link

How to choose

First eliminate options that fail required deployment, license, or use-case constraints; then inspect each detail page for limitations and direct evidence.