BerriAI/litellm - GitHub vs Kome
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. | Kome is a tool for buyers evaluating whether it fits a specific AI workflow. Kome is a versatile AI-powered browser extension designed to enhance your online experience by combining intelligent summarization and efficient bookmarking. Whether you're a student, researcher, marketer, or an avid reader, Kome's seamless integration into popular browsers such as Chrome, Firefox, Edge, Opera, Brave, and soon Safari, allows you to effortlessly save and organize valuable content with its intuitive bookmark manager. Additionally, Kome's AI-Powered Summarizer provides concise and informative summaries of articles, YouTube videos, news, and even Twitter threads, enabling you to quickly grasp key points and optimize your content consumption. Ideal for boosting productivity and collaboration, Kome also includes smart compose features that help you generate emails, tweets, and blog posts using your bookmarks. Experience a more efficient and organized digital life by joining Kome for free today and explore premium options for an even richer feature set. The capabilities to test first are AI-powered summarizer, Smart bookmark manager, AI-assisted writing tools, Cross-browser compatibility, Easy access with search functionality. Those details matter because they determine whether Kome can reduce manual work, replace tool switching, or produce reliable output without constant cleanup. Best-fit users include Students, Professionals, Researchers, Marketers. A useful pilot should include a normal task, an edge case, and a recovery test so the team can see what happens when the first attempt is incomplete. Pricing is listed as Custom, with plan information currently shown as See official site. Confirm current limits, credits, seats, cancellation rules, and commercial terms on the official website before relying on this listing for budget decisions. Before adopting Kome, compare it with adjacent tools in the same category. Measure setup time, output quality, data handling, collaboration controls, exports, and whether non-technical users can repeat the workflow without heavy prompting. The strongest buying signal is not feature count; it is whether Kome consistently completes the exact job the buyer needs with fewer manual handoffs. If sensitive customer, financial, or internal data is involved, review privacy and retention policies before production use. A final buying check for Kome should include a hands-on trial with real inputs, not only vendor screenshots or directory copy. Document the prompt, source files, output, cleanup time, and any errors so the team can compare Kome against another option on equal terms. If the product will be used by a team, test permissions, workspace sharing, exports, notifications, and whether results stay consistent across multiple users. For regulated or customer-facing work, review security claims, data retention, admin controls, and support response expectations before a wider rollout. |
| Category | Developer Tools | BrowserApplication |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Custom |
| Starting Price | N/A | N/A |
| Plans | — |
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| Tags | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys | browser extensionAIbookmark managerAI summarizerYouTube |
| 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 | ||
| AI-powered summarizer | ||
| Smart bookmark manager | ||
| AI-assisted writing tools | ||
| Cross-browser compatibility | ||
| Easy access with search functionality | ||
| User-friendly interface | ||
| Automated organization of bookmarks | ||
| Instant summarization of diverse content | ||
| Enhanced online productivity | ||
| Support for saving and categorizing images and videos | ||
| View BerriAI/litellm - GitHub | View Kome | |
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