Developer Builds AI Router That Splits Prompts Across Multiple Models Automatically

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A developer has released Flint, an open-source AI routing engine designed to eliminate the need for manually selecting large language models for different tasks. Flint analyzes an incoming prompt, breaks it into capability-specific sub-tasks such as research, analysis, and coding, then dispatches each to the most suitable model. The sub-tasks are executed in parallel and their outputs are synthesized into a single coherent response. The backend is built on FastAPI and SQLite, supports over 30 models including DeepSeek and Qwen, and exposes an OpenAI-compatible API requiring only a base URL change. A live demo is available at flintapi.ai without requiring a signup, and the source code has been published on GitHub.

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