Qwen-2.5-72B on serverless inference
Generate responses in a chat with Qwen, a helpful assistant
Discover chat prompts with a searchable map
Generate code and answers with chat instructions
Engage in conversations with a multilingual language model
llama.cpp server hosting a reasoning model CPU only.
Advanced AI chatbot
Chat with a Japanese language model
Chat with Qwen2-72B-instruct using a system prompt
Generate chat responses from user input
Chat with a friendly AI assistant
Interact with a chatbot that searches for information and reasons based on your queries
Generate responses and perform tasks using AI
Qwen-2.5-72B-Instruct is a large language model designed for conversational interactions. It is based on the Qwen-2.5 architecture, scaled up to 72 billion parameters, and optimized for instruction-following tasks. The model is deployed using serverless inference, enabling efficient and scalable interactions through a chat interface.
What makes Qwen-2.5-72B-Instruct different from other models?
Qwen-2.5-72B-Instruct is optimized for instruction-following tasks and leverages serverless architecture for efficient deployment, making it both versatile and scalable.
Can I use Qwen-2.5-72B-Instruct for commercial purposes?
Yes, the model supports commercial use cases, including customer service, content generation, and more, subject to the terms of service.
Do I need special hardware to run Qwen-2.5-72B-Instruct?
No, the model is designed for serverless inference, meaning you can access it without needing dedicated hardware or complex setup.