BerriAI/litellm - GitHub vs Private LLM
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| 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. | Private LLM runs text-based AI models locally on supported iPhones, iPads and Macs. It is a useful alternative for personal writing, summaries and questions when you want an on-device assistant instead of a hosted team workspace. Download a suitable model first; supported models and performance depend on your device and available memory. The US App Store lists a one-time price of $4.99. The developer describes access across supported Apple platforms with Family Sharing for up to six people and no subscription. Check your own store region for the current price and device requirements. Siri and Apple Shortcuts integration can connect the assistant to your existing workflows. The app privacy policy says conversations stay on-device and are not collected by the developer. This is distinct from the product website, which has analytics and a support form, and from the network requests needed to download models. Local processing is useful for controlling your chat data, but it does not establish that every model answer is correct or that every model will run well on every device. |
| Category | Developer Tools | AI Assistant |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Paid |
| Starting Price | N/A | $4.99 in the US App Store |
| Plans | — |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | local AIoffline chatiPhoneiPadMac |
| 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 | ||
| On-device text-based language models | ||
| iPhone, iPad and Mac support | ||
| Offline chat after model download | ||
| Siri and Apple Shortcuts integration | ||
| Customizable system prompts | ||
| One-time purchase without a subscription | ||
| Family Sharing for up to six people | ||
| Conversation export as PDF or text | ||
| View BerriAI/litellm - GitHub | View Private LLM | |
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