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Models/Language/Qwen3.5 4B (Reasoning)
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Alibaba

Qwen3.5 4B (Reasoning)

Released Mar 2026

View Rankings
Hugging Face
Hugging Face
qwenlm.github.io
Intelligence
#213
Coding
#230
Context262K
Parameters4B

Qwen3.5 4B is a compact, high-efficiency language model released by Alibaba in March 2026. As part of the Qwen3.5 small-model series, it is designed to deliver advanced reasoning and multimodal capabilities on consumer-grade hardware. The model represents a significant architectural shift from previous generations, focusing on intelligence density and efficient long-context processing.

Architecture and Innovation

The model utilizes a unique hybrid attention architecture that combines Gated Delta Networks (a linear attention mechanism) with standard softmax attention in a 3:1 ratio. This design allows the model to maintain a constant memory footprint for routine computations while activating full attention only when precise logical overhead is required. Additionally, Qwen3.5 4B is natively multimodal, trained from the foundation using early-fusion on trillions of multimodal tokens, enabling it to process text, images, and video without relying on external adapters.

Capabilities and Context

Despite its small parameter count, Qwen3.5 4B supports a native context window of 262,144 tokens, which is extensible for complex agentic workflows and long-document analysis. It has been refined through Scalable Reinforcement Learning (RL), allowing it to perform deep logical reasoning, advanced coding tasks, and mathematical problem-solving that previously required much larger models. The model provides global linguistic coverage, supporting over 201 languages and dialects with a high degree of cultural nuance.

For optimal performance, it is recommended to use the model with a reasoning-capable parser. While it can handle ultra-long contexts, maintaining a window of at least 128,000 tokens is advised to preserve its sophisticated chain-of-thought and thinking capabilities during inference.

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