Langfa.st vs. Google's Rich Search Results Test
Langfa.st
Langfa.st is a fast and minimal playground for testing and refining AI prompts. It supports over 50 large language models, including OpenAI, Anthropic, Mistral, Cohere, Google, and others — all available instantly without setup. You can insert variables, use Jinja2 templating, and compare outputs across models. There’s no need to sign up or bring your own API keys — it works out of the box. Langfa.st was built to eliminate the friction of existing tools: complicated UIs, required credentials, or overpriced subscriptions. It gives AI teams and prompt engineers a clean, disposable space to experiment, debug, and iterate — all in one tab. Free to use. You only pay if you need more volume or power features.
Google's Rich Search Results Test
Got your structured data and JSON-LD in place? Great, now go test it. Google has a free tool to help you view your search results as they see it - and spot potential errors or areas for improvement.
Reviews
Reviews
| Item | Votes | Upvote |
|---|---|---|
| Works without login or API key | 1 | |
| Supports 50+ models out of the box | 1 | |
| Built-in support for variables and Jinja2 templating | 1 | |
| Instant response, no setup required | 1 | |
| Clean and distraction-free UI | 1 |
| Item | Votes | Upvote |
|---|---|---|
| No custom API key support (yet) | 1 | |
| Not ideal for running complex multi-turn chats | 1 |
| Item | Votes | Upvote |
|---|---|---|
| No pros yet, would you like to add one? | ||
| Item | Votes | Upvote |
|---|---|---|
| No cons yet, would you like to add one? | ||
Frequently Asked Questions
Langfa.st is specifically designed for testing and refining AI prompts with support for over 50 large language models and features like variable insertion and Jinja2 templating. It allows users to experiment without the need for login or API keys, making it very user-friendly for AI teams. In contrast, Google's Rich Search Results Test is focused on validating structured data and JSON-LD for search results, which is not directly related to AI prompt testing. Therefore, if your goal is to test AI prompts, Langfa.st is the better choice.
No, Langfa.st is not designed for structured data testing. It is a tool for testing AI prompts across various language models. On the other hand, Google's Rich Search Results Test is specifically built to help users validate their structured data and JSON-LD implementations. If you need to test structured data, Google's tool is the appropriate choice.
Langfa.st is more user-friendly for AI prompt testing as it requires no login or API keys, supports multiple models out of the box, and has a clean, distraction-free UI. In contrast, Google's Rich Search Results Test is more technical and focused on structured data validation, which may not be as straightforward for users looking to test AI prompts.
Langfa.st is a fast and minimal playground for testing and refining AI prompts. It supports over 50 large language models, including OpenAI, Anthropic, Mistral, Cohere, Google, and others — all available instantly without setup. Users can insert variables, use Jinja2 templating, and compare outputs across models without needing to sign up or provide API keys.
Pros of Langfa.st include: it works without login or API key, supports over 50 models out of the box, has built-in support for variables and Jinja2 templating, provides instant responses with no setup required, and features a clean and distraction-free user interface.
Cons of Langfa.st include the lack of custom API key support at this time and it may not be ideal for running complex multi-turn chats.
Langfa.st is particularly beneficial for AI teams and prompt engineers who need a clean, disposable space to experiment, debug, and iterate on AI prompts without the friction of complicated UIs or required credentials.
Yes, Langfa.st is free to use. Users only pay if they need more volume or access to power features.
Google's Rich Search Results Test is a free tool provided by Google that allows you to test your structured data and JSON-LD. It helps you view your search results as Google sees them and spot potential errors or areas for improvement.
To use Google's Rich Search Results Test, you simply need to visit the tool's website, enter the URL of the page you want to test, and run the test. The tool will display the search results as Google sees them and highlight any errors or areas that need improvement.
The benefits of using Google's Rich Search Results Test include the ability to identify and fix errors in your structured data, ensure your search results appear correctly, and optimize your content for better visibility in search engine results pages.
One limitation of Google's Rich Search Results Test is that it only shows how your search results appear to Google and may not reflect how they appear on other search engines. Additionally, it may not catch all potential errors or issues with your structured data.
