Qwen 3.5 9B

Overview

Alibaba's next-generation dense 9B model with a 262K native context window and an improved toggleable thinking mode. Apache 2.0 licensed.

When to pick this model

• Long-document analysis without RAG
• Multilingual assistants covering 119 languages
• Switching between fast and deep reasoning per request
• Single-GPU production deployments
• Permissive commercial use cases

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	6 GB
Q5_K_M	7 GB
Q8_0	10 GB
FP16 (no quantization)	18 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• 262K native context in a 9B parameter model
• Toggleable thinking mode for cost control
• Strong multilingual performance across 119 languages
• Apache 2.0 license

Limitations

• Fine-tune ecosystem is still less mature than Qwen 2.5
• Thinking mode can be verbose by default

Architecture & training

Architecture: Dense · 9B · Qwen 3.5 · hybrid thinking · 262k native context

Training: Qwen 3 evolution with 262k context and improved thinking. 119 languages.

Quick start

ollama run qwen3.5:9b

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.