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Model Comparison Analysis (Model Compare) ​

Compare models registered in Model Registry side by side to review training configuration, metrics, and loss curves, and select the optimal model before assigning an alias.

Prerequisites ​

  • Account with access to AI Training
  • Model Registry must have 2 or more models in the same category
  • At least one project exists

Step 1. Enter Model Compare ​

  1. Click Evaluation → Model Compare in the left sidebar.
  2. The Compare page opens with the following guidance at the top.

Select a model category and two models to compare their training configuration, metrics, and loss curves.

Model Compare targets only models registered in the Registry, and is used to review differences between versions before assigning an alias. You can proceed to Assign Alias in Model Registry based on the comparison results.

You can also reach this page via the Compare button at the top of the Model Registry list.


Step 2. Select Models to Compare ​

In the Section 1 area, select a category and 2 models to compare. You can compare exactly 2 models at a time.

Selection Fields ​

FieldInput MethodDefaultDescription
Model categoryDropdownSelect categorySelect from categories registered in Model Registry
Model (Option 1)DropdownSelect modelFirst comparison target from models in the selected category
Model (Option 2)DropdownSelect modelSecond comparison target from models in the selected category

Field Behavior ​

ConditionModel (Option 1) / Model (Option 2)
Category not selectedDisabled, placeholder Select model
After category selectedEnabled, shows list of models in that category
  1. Select the category containing the models you want to compare from the Model category dropdown.
  2. Select respective models in Model (Option 1) and Model (Option 2).
  3. Click the Run Comparison button.

Without Model Selection

If no category or models are selected, a guidance area is shown below.

  • Select a model category
  • Select options to compare their configurations, metrics, and training curves.

Step 3. View Model Details ​

After running the comparison, the Model details section displays metadata for both selected models in a 3-column table. The first column shows item names, the second and third columns show Option 1 and Option 2 values respectively.

INFO ​

ItemDescription
ExperimentTraining experiment name
Base modelBase model used for training
StatusModel status
Created atModel registration date and time

PARAMETERS ​

ItemDescription
base_modelBase model identifier
batch_sizeTraining batch size
learning_rateLearning rate
max_lengthMaximum sequence length
max_stepsMaximum training steps
methodTraining method
total_gpusNumber of GPUs used
training_modeTraining mode

Review the differences in configuration values between the two models in each row, and narrow down the candidate version for alias assignment.


Step 4. View Metrics Comparison ​

Compare training result metrics in charts in the Metrics comparison section.

Loss Charts ​

MetricAxes
Training LossY-axis: metric name / X-axis: loss value
Validation LossY-axis: metric name / X-axis: loss value

Compare the training and validation loss trends of the two models side by side to assess convergence speed and overfitting.

Runtime Chart ​

MetricAxes
Training Runtime (s)Y-axis: metric name / X-axis: time in seconds (s)

Compare training time to also evaluate resource efficiency.

Comparison Metric Summary ​

MetricDescription
Training LossLoss on training data
Validation LossLoss on validation data
Training RuntimeTotal training time (seconds)

Step 5. Use Comparison Results (Assign Alias) ​

Once you've selected the superior model through comparison, assign an alias in Model Registry.

  1. Go to Evaluation → Model Registry.
  2. Click Assign Alias on the relevant category detail page.
  3. Assign an appropriate alias — Best, Active, or Custom — based on the comparison results.
AliasDescription
BestBest-performing version
ActiveCurrently in-use version
CustomUser-defined alias

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