BerriAI/litellm - GitHub vs Vmake

Side-by-side comparison · Updated October 2026

 BerriAI/litellm - GitHubBerriAI/litellm - GitHubVmakeVmake
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.Vmake.ai is an all‑in‑one AI video and media toolkit built for talking head videos and social content. It streamlines video creation with auto captions, watermark and background removal, AI enhancement and upscaling, noise reduction, and multi‑format editing. Create from text, images, or existing clips using integrated models like Veo 3.1, KLING 2.0, and Sora 2, and speed production with batch processing and an app‑only AI teleprompter—ideal for creators, marketers, and e‑commerce teams.
CategoryDeveloper ToolsVideo Editing
RatingNo reviewsNo reviews
PricingOpen SourceFreemium
Starting PriceN/AFree
Plans—
  • Free — Free
  • Plus — $9.99/mo
  • Pro — $29.99/mo
Use Cases
  • Developers
  • Enterprises
  • Startups
  • Educational Institutions
  • YouTube creators
  • E‑commerce teams
  • Social media managers
  • Educators & coaches
Tags
AI gatewayPython SDKLLM routingMCP gatewayvirtual keys
AI videomedia toolkittalking head videossocial contentauto captions
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 video generator (text‑to‑video, image‑to‑video, video‑to‑video)
Auto captions and speech‑to‑text transcription
AI watermark and text/logo/timestamp removal
Video background removal and replacement
AI video enhancement and noise reduction
Video upscaling and resolution improvement
AI teleprompter (app‑only) for natural script reading
Talking Photo to create talking head videos from images
AI thumbnail generator for YouTube and social media
Batch processing for repetitive edits
Multi‑format, multi‑aspect video editing
 View BerriAI/litellm - GitHubView Vmake

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