New API vs Whisper (OpenAI)
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. | Whisper is a cutting-edge automatic speech recognition (ASR) system created by OpenAI. Trained on 680,000 hours of multilingual and multitask supervised data from the web, Whisper boasts improved robustness to accents, background noise, and technical language. It provides transcription services in multiple languages and translates those languages into English. Whisper uses an encoder-decoder Transformer architecture that captures 30-second audio chunks, converts them to log-Mel spectrograms, and predicts corresponding text captions. Its large and diverse dataset helps Whisper outperform existing systems in zero-shot performance across diverse scenarios. |
| Category | Developer Tools | Speech-To-Text |
| 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 | Automatic Speech RecognitionASRSpeech RecognitionTranscriptionTranslation |
| 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 | ||
| High robustness to accents and background noise | ||
| Supports multiple languages | ||
| Translates languages into English | ||
| Encoder-decoder Transformer architecture | ||
| Processes 30-second audio chunks | ||
| Predicts text captions with special tokens integration | ||
| Improved zero-shot performance | ||
| Open-source with detailed resources | ||
| Enables voice interfaces for applications | ||
| Outperforms on CoVoST2 for English translation | ||
| View New API | View Whisper (OpenAI) | |
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