Search the full model catalog.

Qwen3.6-27B is a 27B dense vision-language model from Qwen for agentic coding and reasoning, with optional thinking traces in outputs. On Wiro a request takes about 25K input tokens and returns up to 16K.

Grok 4.1 Fast by xAI is a long-context chat model built for tool calling and agent workflows. It can analyze images and return grounded text answers with sources.

Grok 4.20 is xAI’s flagship text model with a 2M-token context window, tool calling, and structured JSON outputs. Attach images for vision Q&A and OCR.

Decensored Qwen3.5-4B checkpoint for chat, coding, and analysis. Supports optional thinking traces and sampling controls for output style. On Wiro a request takes about 72K input tokens and returns up to 16K.

A large language model optimized for chat interactions and logical reasoning tasks. Designed for developers and researchers.

Qwen3.5-4B is the 4B model of Qwen's Qwen3.5 line. A Thinking field turns its reasoning pass on or off, and Wiro gives it room for 72,704 input tokens per request.

A dense 9-billion parameter language model optimized for chat and reasoning tasks. Designed for efficient deployment and high-quality responses.

A decensored build of Qwen3.5-27B, made with Heretic, a tool that edits the model's weights to cut refusals. Text chat with an optional thinking mode and function calling.

The smallest model in ByteDance's Seed 2.0 series, a reasoning LLM that reads images and calls functions. Reasoning is on by default and can be switched off for simple jobs.

A lightweight ByteDance language model for chat and tool calling, with image understanding and a 256K-token context window.

Qwen3.5-27B is a 27B model from Qwen's Qwen3.5 line that always reasons before it replies and can call your functions. Qwen reports 72.4 on SWE-bench Verified for it.

Requests here run Gemini 3.1 Pro Preview, which Google built on Gemini 3 Pro's sparse mixture-of-experts design. One request can hold up to 1M tokens of mixed text, audio, video, images and documents.

GLM-4.7-Flash is a 30B-A3B mixture-of-experts language model from Z.ai. It writes out its reasoning before answering, and Z.ai recommends it mainly for frontend and backend coding.

GPT-5 Nano is a GPT-5 model that OpenAI describes as a good fit for summarization and classification. It reads text and up to 10 images and supports function calling, web search and structured output.

AI model for processing text prompts and image inputs with advanced reasoning capabilities. Supports multi-modal inputs and customizable responses.

A compact AI model optimized for text generation tasks, designed for efficient processing and accurate responses.

Google's Gemini 3 Flash reads text, images, video, audio and documents and answers in text. It is built on Gemini 3 Pro, with a thinking level you can set from minimal to high.

Google's Gemini 2.5 Flash reads text, images, video and audio and answers in text, with adjustable thinking, function calling and JSON schema output over a context of about one million tokens.

Chat with one branch of a GitHub repository: its files are indexed, and the closest matches go to the chat model you select. Each run needs a GitHub access token, public repositories included.

Ask questions about a YouTube video and get answers drawn from its captions, using a chat model you pick. Videos without captions are transcribed from their audio first.