> For the complete documentation index, see [llms.txt](https://ai-docs.fptcloud.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai-docs.fptcloud.com/fpt-ai-studio/services/model-testing-test-jobs.md).
# Model Testing - Test Jobs
## What is Model Testing - Test Jobs?
**Model Testing - Test Jobs** is a core feature of the FPT AI Factory Portal that provides a structured and automated way to evaluate fine-tuned AI models. Unlike **Interactive Sessions** - which focus on real-time, manual interactions, **Test Jobs** are designed for large-scale, repeatable testing using predefined datasets.
**Key capabilities of Test Jobs:**
* **Automated Evaluation:** Run large-scale tests using structured input data to evaluate model responses without manual intervention.
* **Custom Test Sets:** Upload domain-specific datasets tailored to your business cases (e.g., custom queries, legal documents, medical records)
* **Standardized Test Sets:** Leverage publicly available benchmarks developed be researchers to evaluate models against industry standards (e.g., Nejumi Leaderboard 3, LM Evaluation Harness, VLM Evaluation Kit)
* **Performance Metrics:** Analyze model outputs using quantitative and qualitative metrics.
**Model Testing - Test Jobs** ensures that your AI model is not only responsive in live interactions but also robust, consistent, and scalable across a wide range of inputs. It’s an essential step before deployment, especially for high-stakes applications in industries like finance, healthcare and legal services.
## When to Use Model Testing - Test Jobs?
**Model Testing - Test Jobs** is most valuable when you need to evaluate the overall performance, reliability, and scalability of a fine-tuned model before deployment.
You should use **Test Jobs** when:
* You want to validate model performance **at scale**.
* You want to track improvements **across model versions**.
* You require **quantitative performance metrics**.
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