3DFY.ai vs BerriAI/litellm - GitHub
Side-by-side comparison · Updated October 2026
| Description | 3DFY.ai harnesses generative artificial intelligence to transform text descriptions into high-quality 3D models, simplifying and democratizing the process of 3D content creation. Its AI-powered technology surpasses traditional 3D creation methods like photogrammetry and manual design by offering scalability, speed, and cost-efficiency, making it accessible to a wide range of users from individuals to businesses. | 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. |
| Category | 3D Modeling | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Pricing unavailable | Open Source |
| Starting Price | N/A | N/A |
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| Tags | AIgenerativetext to 3D3D modelscost-efficient | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys |
| Features | ||
| Generative artificial intelligence for 3D model creation | ||
| Creates high-quality 3D models from text descriptions | ||
| Overcomes limits of traditional 3D content creation methods | ||
| Proprietary AI-powered 3D generation pipeline | ||
| Designed for uncompromised 3D asset quality | ||
| Automated creation of high-quality 3D models | ||
| Expressive and scalable 3D modeling solutions | ||
| Caters to both individual self-expression and business use cases | ||
| Enables instant creation of 3D models with 3DFY Prompt | ||
| Offers 3DFY Prompt, 3DFY Megapacks, and 3DFY Image services | ||
| 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 | ||
| View 3DFY.ai | View BerriAI/litellm - GitHub | |
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