BerriAI/litellm - GitHub vs SparkReceipt
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. | SparkReceipt offers comprehensive management of cookies, providing users with detailed information about the different types of cookies used on the website and the ability to control their privacy settings. The platform categorizes cookies into Necessary, Preferences, Statistics, and Marketing, and allows users to select the types of cookies they wish to allow. Detailed descriptions of specific cookies used by the site are provided, helping users make informed decisions about their cookie preferences. |
| Category | Developer Tools | Privacy Management |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Free |
| Starting Price | N/A | N/A |
| Plans | — |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | cookie managementprivacy settingsstatisticsmarketingpreferences |
| 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 | ||
| Manage cookie preferences | ||
| Detailed cookie descriptions | ||
| Control over Necessary, Preferences, Statistics, and Marketing cookies | ||
| Enhanced privacy settings | ||
| Real-time content adjustments | ||
| Localized user experience | ||
| User behavior analytics | ||
| Compliance with cookie regulations | ||
| Integration with third-party services | ||
| Optimized user interactions | ||
| View BerriAI/litellm - GitHub | View SparkReceipt | |
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