Qwen3.5-9B Language Model

Overview

Qwen3.5-9B is a dense 9-billion parameter language model optimized for chat and reasoning tasks. It is designed for efficient deployment with support for various inference parameters to customize behavior.

What you can build

This model is ideal for building conversational agents, chatbots, and reasoning-based applications where balanced performance and accuracy are required.

Inputs

• prompt: Text input to generate a response from the model
• thinking: Enable or disable reasoning mode
• user_id (optional): Unique identifier for maintaining chat history
• session_id (optional): Session identifier for managing multiple chat sessions
• system_prompt (optional): System-level instructions to guide model behavior
• temperature, top_p, top_k, repetition_penalty, length_penalty: Parameters to control output randomness and structure
• max_tokens, min_tokens: Limits on token generation
• stop_sequences: Stop generation when encountering specified strings
• seed: For reproducible outputs
• quantization: Enable quantization for reduced memory usage
• do_sample: Toggle between deterministic and probabilistic sampling

Outputs

• Generated text responses based on the input prompt and configuration parameters

Recommended settings

For balanced performance and coherence, start with default values for temperature (0.7), top_p (0.95), and max_tokens (0). Adjust based on application requirements.

Limitations

• Not optimized for extremely long contexts
• Output quality depends on training data and parameter tuning
• Quantization may slightly reduce output quality

Safety & compliance

This model adheres to safety guidelines by default. Ensure compliance with applicable regulations and consider additional safeguards for sensitive applications.