BerriAI/litellm - GitHub vs Devv 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. | Devv AI is a specialized AI search engine designed to boost developer productivity by delivering quick and precise solutions to programming queries. Leveraging large language models (LLMs) and a curated index of developer-centric resources, it offers more relevant results compared to traditional search engines. With modes like Web, Chat, GitHub, and Expert, it supports tasks ranging from code refactoring to complex problem-solving. It also integrates with GitHub and other developer tools, making it a comprehensive solution for debugging, code completion, learning new technologies, and more. |
| Category | Developer Tools | Developer Tool |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Freemium |
| Starting Price | N/A | Free |
| Plans | — |
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| Use Cases |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | AI search enginedeveloper productivityprogramming querieslarge language modelsdeveloper-centric resources |
| 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 | ||
| Multiple Search Modes: Offers distinct search modes like Web, GitHub, Expert, and Chat Mode, each tailored for specific development use cases. | ||
| Programming Language Specificity: Allows specifying programming languages for tailored responses. | ||
| Integration with Popular Platforms: Connects with Stack Overflow, GitHub, and DevDocs. | ||
| Advanced AI Model Integration: Utilizes models like GPT-4 for comprehensive answers. | ||
| Personalized Search and History: Adapts and learns from user interactions. | ||
| Continuous Learning and Improvement: Enhances its responses based on user feedback. | ||
| Code Generation and Refactoring: Assists with code creation and improvement. | ||
| Image Analysis: Aids in code debugging and planning (though not currently available). | ||
| Goal-Based Agents: Provides AI support for specific tasks like debugging. | ||
| Planned VSCode Plugin: Offers integration for Visual Studio Code. | ||
| View BerriAI/litellm - GitHub | View Devv AI | |
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