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A finished training run produces a LoRA adapter, which is a small set of weight deltas. To use the model anywhere on BenchGen, you merge the adapter into its base model to get a standalone checkpoint, then push that checkpoint to the platform. Once saved, the model appears in your Models list with a ready inference endpoint.

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Two actions after training

When a run completes, the Actions panel offers two things:
You don’t have to merge just to test the model. Train can run inference against the adapter directly. See Run inference.

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Steps

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1. Open the completed run

Go to Train → Jobs and open the completed job. The Actions panel reads “Model ready — select an action below”. The completed run with the Actions panel ready

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2. Merge the adapter

Under Merged Model, click Merge Model. Merging starts, the panel shows “Merging in progress…”, and a new entry appears in Export History with a Preparing badge. This usually takes a couple of minutes. Merging in progress with a new Export History entry

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3. Name the model

When the merge is ready, click Save on Platform on the Export History entry. In the Name this model on BenchGen dialog, enter the name the model will appear under (for example Qwen3-0.6B_math), then click Push to BenchGen. The Name this model dialog before pushing to BenchGen

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4. Confirm it’s saved

The Export History entry updates to Ready and Pushed, with a Saved on Platform check. You can also Download the merged checkpoint from here. The Export History entry marked Pushed and Saved on Platform

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5. Use the model

The saved model now appears in Models as a deployed, ready endpoint. Open it to Run Inference or evaluate it. Its endpoint panel shows the LiteLLM Name, Endpoint URL, access Token, and a SAFETENSORS format. The saved model card with a ready endpoint

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Next Steps

Your model is saved on BenchGen and ready to use. Head over to Eval to serve it as a live endpoint, then benchmark it against an environment.

Deploy an inference model

Spin up a live, OpenAI-compatible endpoint for your saved model.

Evaluate an inference model

Benchmark the running model against an environment and read the scores.
Last modified on June 26, 2026