BerriAI/litellm - GitHub vs Teste.ai
Side-by-side comparison · Updated October 2026
| Description | LiteLLM is an AI gateway and Python SDK from Berrie AI Incorporated, published in the BerriAI GitHub repository. The SDK provides a common interface for model calls inside Python applications. The proxy gateway centralizes access for a team, with virtual keys, model routing, spend tracking, budgets and an administration interface. The official documentation lists support for more than 100 model providers. Supported endpoints and features vary by integration, so verify your model’s streaming, tool-calling, image, audio or embedding requirements. The router supports retries, fallbacks and load balancing; observability integrations can send request data to tools such as Langfuse, LangSmith and OpenTelemetry. LiteLLM also provides an MCP gateway. It can connect upstream servers using Streamable HTTP, SSE or stdio, expose tools through a fixed gateway endpoint, and scope access by key, team or organization. This requires configuring the upstream servers and authentication; the gateway does not automatically grant access to third-party tools. Agent-to-agent integrations are documented separately. The open-source offering has no software license fee for self-hosting. Code outside the enterprise directory is MIT-licensed, while enterprise code has separate terms. Enterprise pricing is quoted by annual gateway request capacity, deployment architecture and support needs, rather than a per-token license charge. Model-provider charges and infrastructure costs still apply. Enterprise adds controls and support such as SSO, SCIM, audit logs and service-level agreements. Compare New API for another self-hosted gateway with provider-channel management and usage accounting. Evaluate a representative workload, inspect request logging and secret handling, test budget and failure behavior, and decide whether SDK integration or a shared gateway best fits your application. | Welcome to teste.ai, an innovative AI-based software testing toolkit designed to revolutionize your testing processes. With teste.ai, you can increase productivity and save time by generating test plans, scenarios, test cases, and steps from a single requirement. It supports various testing types, including API, functional, security, and performance testing. The tool also excels in generating database queries and structured data sets quickly and accurately. Integration with advanced AI models ensures precision and relevance in test case generation, elevating your testing efficiency and quality. The platform offers unmatched speed, reliability, and facilitates efficient team collaboration with its intuitive dashboard. |
| Category | Developer Tools | Natural Language Processing |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Paid |
| Starting Price | N/A | $10/mo |
| Plans | — |
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| Use Cases |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | AI-basedsoftware testingtest plansscenariostest cases |
| Features | ||
| Python SDK for direct application integration | ||
| Shared AI proxy gateway and administration UI | ||
| More than 100 documented model-provider integrations | ||
| Virtual keys, users, teams, budgets and rate limits | ||
| Spend tracking and observability integrations | ||
| Router retries, fallbacks and load balancing | ||
| MCP gateway for Streamable HTTP, SSE and stdio upstreams | ||
| Key, team and organization MCP permissions | ||
| Separate enterprise identity, audit and support features | ||
| AI-powered test plan generation | ||
| Comprehensive testing types (API, functional, security, performance) | ||
| Natural language database query generation | ||
| Rapid structured data set creation | ||
| Advanced AI model integration | ||
| Unmatched speed and reliability | ||
| Efficient team collaboration | ||
| Intuitive dashboard | ||
| Automatic test case generation | ||
| Boundary value and usability testing | ||
| View BerriAI/litellm - GitHub | View Teste.ai | |
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