BerriAI/litellm - GitHub vs Spot
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. | Spot AI offers an advanced video intelligence and surveillance solution that leverages AI to enhance security, manage incidents, and improve operational efficiency. The system includes high-resolution, NDAA-compliant IP cameras, a cloud-based dashboard for centralized management, and Intelligent Video Recorders (IVRs) for 24/7 local storage with on-edge AI processing. Its intuitive AI Copilot feature assists users in automating video workflows and extracting actionable insights rapidly, making it suitable for various industries including manufacturing, healthcare, and retail. The platform integrates seamlessly with existing systems, ensuring quick setup and scalability. |
| Category | Developer Tools | SecurityApplication |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Pricing unavailable |
| Starting Price | N/A | N/A |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | AIvideo intelligencesurveillancesecurityincident management |
| 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 | ||
| High-resolution, NDAA-compliant IP cameras | ||
| AI Copilot for automated video workflows | ||
| Cloud-based management dashboard | ||
| 24/7 local storage with Intelligent Video Recorder (IVR) | ||
| Rapid incident resolution | ||
| Seamless integration with existing systems | ||
| Scalable to any number of cameras | ||
| Security-by-design | ||
| Advanced AI alerts and intelligence dashboards | ||
| Quick setup process | ||
| View BerriAI/litellm - GitHub | View Spot | |
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