Chat with a checkpoint

tp serve start run:run-4f2a91 --gpus 1
tp serve ls

Starts an OpenAI-compatible vLLM server from that run’s export and prints its endpoint and token. Then open the console’s Playground page and chat. A Playground Session is for a person to try a model. For application traffic, use a Model Deployment instead.

Start one

CLI
Console

tp serve start run:run-4f2a91 --gpus 1        # a training artifact
tp serve start Qwen/Qwen3.5-9B --gpus 2       # any hub model
tp serve start /shared/models/my-model        # a path on shared storage

--gpus is the tensor-parallel size.

Manage it

tp serve ls                              # your services, with endpoints and remaining TTL
tp serve extend run-4f2a91 --hours 4     # keep it alive longer
tp serve stop run-4f2a91                 # stop it and release the GPUs

A session holds real GPUs and counts against your quota. It has an idle TTL, set by the deployment, and stops on its own when that expires. That is the protection against starting one and forgetting it, not a fault. Extend it if you still need it.

Compare two models side by side

The Playground sends one prompt to two services at once, which is the fastest way to see what an alignment stage actually changed. Start two sessions — the SFT artifact and the GRPO artifact — and pick both in the A/B selector. Chat controls are temperature, max tokens and a system prompt. The endpoints are OpenAI-compatible, so anything that speaks that API can use them:

curl https://tuneplane.your-company.com/inference/<id>/v1/chat/completions \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{"model": "default", "messages": [{"role": "user", "content": "Hello"}]}'

Which backends can serve

Fleet kind	Session form
`kubernetes`	A standalone vLLM Pod, not a RayJob, reached through the Kubernetes API proxy
`node`	A vLLM container on a registered Node, with a reserved port reachable from the control plane
`slurm`	Not supported: compute nodes usually have no inbound path from the console

Check it worked

tp serve ls shows the session with an endpoint and a TTL. If it stays pending, the weights are still loading — a 9B model takes a minute or two on a cold cache. The Playground is a premium feature an administrator enables per role or user. When it is not enabled, the page explains that rather than erroring.

Model deployments for application traffic · Model registry · The Playground page

Get started

Core concepts

Train a model

Evaluate and serve

Agent environments

Extend the platform

Collaborate

Integrations

Reference

Help

Chat with a checkpoint

Start one

Manage it

Compare two models side by side

Which backends can serve

Check it worked

Next

​Start one

​Manage it

​Compare two models side by side

​Which backends can serve

​Check it worked

​Next

Start one

Manage it

Compare two models side by side

Which backends can serve

Check it worked

Next