BerriAI/litellm - GitHub vs Raz

Side-by-side comparison · Updated October 2026

 BerriAI/litellm - GitHubBerriAI/litellm - GitHubRazRaz
DescriptionLiteLLM 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.The webpage https://www.tryraz.com/request-a-demo provides a platform for users to request a demo for TryRaz's lead engagement software. The CSS styling on the page focuses on enhancing text readability, providing responsive adjustments, and maintaining clean, uncluttered display elements. Key styles include font smoothing, color inheritance for links, zero margin for rich text elements, centered containers, text overflow ellipsis for multi-line text, and multiple classes for hiding elements based on screen size. Additionally, the page hides scrollbars in WebKit browsers and includes utility classes for margin and padding adjustments.
CategoryDeveloper ToolsLead Engagement Software
RatingNo reviewsNo reviews
PricingOpen SourcePricing unavailable
Starting PriceN/AN/A
Use Cases
  • Developers
  • Enterprises
  • Startups
  • Educational Institutions
  • Sales Teams
  • Marketing Departments
  • Web Developers
  • Product Managers
Tags
AI gatewayPython SDKLLM routingMCP gatewayvirtual keys
lead engagement softwaredemo requestCSS stylingresponsive designclean display
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
Font smoothing for crisper text
Color inheritance for links
Zero margin for first and last rich text elements
Center alignment for various container sizes
Text overflow ellipsis for 2 and 3 lines
Responsive hide classes based on screen width
Scrollbar hiding for WebKit browsers
Indented paragraph style
Zero margin and padding utility classes
Custom styles for menu links on smaller devices
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