FW-Qwen3.5-27B

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About this model

Qwen3.5-27B is a post-trained causal language model with a vision encoder from Alibaba's Qwen3.5 family. Qwen3.5 integrates multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility. It uses a 64-layer hybrid stack with Gated DeltaNet and Gated Attention blocks, supports text and image inputs in the official model card, and supports 201 languages and dialects.

Key model capabilities

• Unified vision-language foundation with early-fusion multimodal training
• Hybrid Gated DeltaNet and Gated Attention architecture
• Thinking mode by default, with configurable non-thinking mode
• Tool use through Qwen-Agent, SGLang, and vLLM examples
• Support for 201 languages and dialects
• Native 262,144-token context, extensible to 1,010,000 tokens with YaRN
• Multi-Token Prediction (MTP) support