Qwen3.5 27B (Reasoning) is a dense, multimodal language model released by Alibaba's Qwen team in February 2026. Part of the Qwen3.5 "Medium" series, it is designed to achieve high intelligence-per-compute, specifically targeting "agentic" tasks that require complex multi-step planning and logical consistency. Unlike the Mixture-of-Experts (MoE) models released in the same series, the 27B variant is a dense architecture optimized for high performance and efficient local deployment.
The model features a hybrid architecture that combines Gated Delta Networks (linear attention) with standard Gated Attention mechanisms across 64 layers. This design enables high-throughput processing and efficient memory usage, supporting a native context window of 262,144 tokens, which is extensible up to 1,010,000 tokens. It operates as a unified vision-language foundation, utilizing early-fusion training to achieve parity across text and visual understanding benchmarks.
Post-training for Qwen3.5 27B involves a four-stage pipeline, including long Chain-of-Thought (CoT) cold starts and reasoning-based reinforcement learning (RL). This process enables the model to generate internal reasoning tokens to solve complex mathematical, coding, and logical problems. To capture this internal thinking process effectively, it is recommended to use a compatible reasoning parser (such as qwen3) during inference.
Global accessibility is a core feature, with expanded support for 201 languages and dialects. The model's training infrastructure utilizes asynchronous RL frameworks and next-generation multimodal efficiency, allowing it to maintain logical structure and factuality over long-horizon tasks and complex agentic workflows.