ActionTogether AIUpdated September 2026
Which models are available on Together AI?
Short answer: You can list models in Together AI by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Together AI List Models action to a workflow, map its 0 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.
Sample request
{}
Returns
{"data": [{"id": "model-1","object": "model"}]}
Use these fields in downstream nodes for routing, logging, or error handling.
Triggered by
Apps that pair well as the trigger for List Models.
Any of these apps can fire this action as part of a workflow.
FAQ
Questions about List Models.
What does the List Models action do in Together AI?
Lists models available on Together AI with their type (chat, language, embeddings, image) and pricing tier. Useful for surfacing a dynamic model picker.
What inputs does List Models require?
List Models has no required inputs. Sensible defaults are applied if you leave fields blank.
Can I use dynamic inputs from earlier workflow nodes?
Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.
What happens if Together AI returns an error?
The run history shows the failed step with its input and the error message Together AI returned, so you can fix the input and run the workflow again. Automatic retries are built into HTTP steps only, where you can also set your own retry count and delay.
Does List Models support batch operations?
Run List Models inside a loop to process each item in an array. TinyCommand does not throttle calls for you, so for large arrays add a Delay step if you need to stay within Together AI's rate limits.
More actions
Other Together AI actions.
Action
Chat Completion
Runs an open-weight chat model (Llama 4, DeepSeek-V3, Qwen, Mixtral, etc.) on Together AI's fast inference platform. OpenAI-compatible request shape so existing chat-completion code mostly works as is.
ActionCreate Embeddings
Generates vector embeddings using one of Together's open-weight embedding models (e.g. BGE, M2-BERT, UAE). Use for RAG, semantic search, or clustering pipelines.