As we dive deeper into 2025 with more complex AI workflows, testing APIs for model deployments has become crucial. If you’re tired of Postman’s syncing issues or bloated interface when working with Hugging Face endpoints, you’re not alone. I’ve been exploring the best Postman alternatives optimized for AI devs like us focusing on speed, offline capabilities, and seamless integration with tools like Transformers library.
Here’s my quick rundown of top picks:
-
Bruno: Lightweight and Git-friendly, perfect for version-controlling your API requests during model fine-tuning sessions. Great for solo AI experimenters.
-
Hoppscotch: Open-source and browser-based—ideal for quick tests on Hugging Face Spaces without installing anything.
-
Insomnia: Robust for GraphQL and REST APIs, with strong support for environment variables that shine in multi-model testing.
-
Thunder Client: VS Code extension that’s a game-changer if you’re scripting API calls alongside your Python notebooks.
But after testing them all with real Hugging Face inference endpoints, Apidog emerges as my number one go-to. Its all-in-one platform handles API design, mocking, and debugging with AI-specific features like auto-generated OpenAPI docs tailored for ML pipelines saving me hours on collaborative projects. Plus, it’s fully offline-capable, so no more cloud dependency during sensitive model evals.
What are you using for Postman alternatives in your AI API workflows? Share below—let’s crowdsource the ultimate stack for 2025!