Microsoft Cognitive Toolkit vs New API
Side-by-side comparison · Updated October 2026
| Description | The Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning toolkit developed by Microsoft. It allows users to efficiently train deep learning models with flexible architecture and scalability. CNTK can be used for machine learning tasks such as image recognition, speech processing, and text analytics. It supports both CPU and GPU, making it versatile for different computing needs and leverages various languages including C++, C#, and Java. | 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. |
| Category | Machine Learning | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Free | Open Source |
| Starting Price | Free | N/A |
| Plans |
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| Tags | deep learningmachine learningimage recognitionspeech processingtext analytics | AI gatewayLLM routingmodel managementrate limitingusage accounting |
| Features | ||
| Open-source | ||
| Supports multiple programming languages | ||
| CPU and GPU compatible | ||
| Scalable and flexible architecture | ||
| Suitable for real-time applications | ||
| Extensive documentation | ||
| Community support | ||
| Versatile for various industries | ||
| Developed by Microsoft | ||
| Efficient model training | ||
| 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 | ||
| View Microsoft Cognitive Toolkit | View New API | |
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