Browsing models
The dashboard’s Models view lists every model currently served, with its provider, size, and per-request price. You can search and sort (e.g. cheapest first). Programmatically, list models via the API:model in your request), how many nodes serve it, and its price.
Model families
The grid serves several kinds of model, shown as coloured categories in the dashboard:- Language — general chat / instruct models (Llama, Qwen, Gemma, Mistral, Phi …).
- Code — programming-tuned models (Qwen Coder) with OpenAI tool-calling.
- Reasoning — chain-of-thought models (DeepSeek R1) that “think” before answering; their reasoning shows in a collapsible box in chat.
- Embeddings — text-to-vector models for search and RAG. These use a separate endpoint and are not for chat — see the Embeddings guide.
model id changes.
Choosing a model
- Smaller models (e.g. 3B-class) are cheapest and fastest — great for classification, extraction, drafting, and agent steps.
- Larger models trade cost/latency for capability.
- Reasoning models are best for math, logic and multi-step planning.
- Availability matters — a model with more serving nodes is more resilient. Prefer models with redundancy for production.
OpenAI compatibility
Model ids are passed exactly like OpenAI’smodel field. If your code already targets the OpenAI API, switching a model is just changing that string (and the base URL — see the API guide).
The catalog grows as operators bring more models online. Want a model served? Run a node and serve it, or ask the community.
