Understanding SQAI Tokens: What They Are & What You Get

At SQAI Suite, we work with multiple large language models (LLMs) behind the scenes to help you streamline and enhance your Quality Assurance processes. Each of these models has its own way of calculating token usage for both inputs (e.g., reading or analyzing content) and outputs (e.g., generating test cases or scripts).

To simplify things for you, we’ve introduced SQAI Tokens — a unified, average-based token system that represents how much processing power you're using across all the smart features in our platform.

SQAI Tokens are a standardized unit we use to measure LLM usage across different tasks in SQAI Suite. Whether you're pulling in user stories from JIRA, chatting with our AI assistant, generating test cases, analyzing code repositories, or producing automated test scripts — SQAI Tokens are what fuel those actions.

Because different LLMs handle tokens differently (some are more efficient for inputs, others for outputs), we’ve averaged out the usage across all models to give you one simple and fair metric: SQAI Tokens.

To help you understand how far your tokens go, here’s an average breakdown of what you can expect in return for your SQAI Token usage:

These are average values, based on typical use cases across multiple LLMs. Actual usage may vary depending on the complexity of your stories, code, or scripts.

Your SQAI Tokens are consumed during various activities across the platform, including:

Every action that requires language model processing uses SQAI Tokens — making it easy for you to keep track of how much intelligence power you’re consuming. In the statistics page, you can always keep track of the amount of SQAI Tokens you have used so far.