New API vs TensorFlow
Side-by-side comparison · Updated October 2026
| Description | New API is a self-hosted AI gateway and model-management project maintained in the QuantumNous repository. It brings provider channels, access tokens, model restrictions, usage statistics and cost accounting into one interface. Teams supply their own authorized model-provider access and operate the gateway in their chosen environment. The gateway supports several API formats, including OpenAI-compatible requests, Claude Messages and Google Gemini. Compatibility has boundaries: the README marks Gemini-to-OpenAI conversion as text-only without function calling, and OpenAI-compatible to Responses conversion as in development. Test the exact endpoints, streaming behavior and tool calls your application uses before switching traffic. Routing features include weighted channel selection, automatic retry after failures and user-level model rate limits. The dashboard supports request-based, usage-based and cache-hit cost accounting, with token grouping and model-access controls. These controls can help organize usage, but retries and a common API format do not guarantee uninterrupted service or identical behavior across providers. The current repository license is AGPLv3. Docker Compose is the recommended quick-start path in the README, which also documents Docker commands with SQLite or MySQL. Running the software still involves infrastructure, operations and upstream model charges. Review the current license, secure your deployment and validate accounting against provider bills. Compare LiteLLM if you also want a Python SDK or a documented gateway for MCP servers and agents. | TensorFlow is an open-source platform developed by Google for machine learning and artificial intelligence research. TensorFlow provides a range of tools, libraries, and resources to help developers effectively build and deploy machine learning models on various platforms, including web, mobile, and edge devices. The comprehensive API and rich ecosystem support diverse applications and facilitate easy exploration of machine learning concepts and real-world implementations. |
| Category | Developer Tools | Machine Learning |
| Rating | No reviews | No reviews |
| Pricing | Open Source | Free |
| Starting Price | N/A | Free |
| Plans | — |
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| Tags | AI gatewayLLM routingmodel managementrate limitingusage accounting | Machine LearningAITensorFlowGoogleOpen-source |
| Features | ||
| Self-hosted AI gateway and model management | ||
| Provider channels, token groups and model restrictions | ||
| OpenAI-compatible, Claude Messages and Gemini format support | ||
| Documented limits on protocol conversion | ||
| Weighted channel selection and failure retries | ||
| User-level model rate limiting | ||
| Request, usage and cache-hit cost accounting | ||
| Docker Compose deployment documentation | ||
| Open-source platform | ||
| Comprehensive API | ||
| Support for web, mobile, and edge devices | ||
| Extensive libraries | ||
| Tutorials and guides | ||
| Educational resources | ||
| Production-ready pipelines with TFX | ||
| Develop web ML applications with TensorFlow.js | ||
| Deploy models on mobile with TensorFlow Lite | ||
| Enhanced services through cookies | ||
| View New API | View TensorFlow | |
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