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LatestQwen · Alibaba3.5
Qwen · AlibabaVision-Language

Alibaba's Qwen team releases 4B vision-language model

The new Qwen3.5-4B model combines text and image understanding in a compact, permissively licensed package for developers.

Feb 27, 2026
NotableApache 2.0
Qwen3.8-27B

The Qwen team at Alibaba has released Qwen3.5-4B, a new 4-billion-parameter model that marks the debut of their Qwen3.5 family. Released under the permissive Apache 2.0 license, the model is designed for instruction-following tasks that involve both text and images.

As a vision-language model (VLM), Qwen3.5-4B can process and understand visual information alongside natural language prompts. This enables applications like describing the content of a photo, answering questions about an image, or following complex instructions that reference visual elements.

The release is notable for its combination of compact size and open access. A 4B parameter count makes the model more accessible for developers and researchers who may not have access to large-scale GPU clusters. Paired with the commercially-friendly license, Qwen3.5-4B represents another strong contender in the growing field of smaller, capable open-source multimodal models.

This release is the first in the Qwen3.5 series, setting the stage for potential future models in the family. Developers can access the model card, weights, and usage examples directly from the official Hugging Face repository.

Sources

  • Qwen/Qwen3.5-4B

    Hugging Face

    Visit
OlderQwen Releases 9B Multimodal Model in New 3.5 SeriesQwen · Alibaba · Vision-Language · 8 months agoNewerIBM Releases 1B Granite Model for Multilingual SpeechIBM · Speech → Text · 8 months ago

Get the model

Hugging Face

Specs

Parameters4B
Context window262K tokens
Size9.3 GB
PrecisionBF16
ArchitectureQwen3_5ForConditionalGeneration
LicenseAPACHE-2.0
Downloads4.6M
Likes3.1K

Can you run it?

Runs on a laptop — about 4.9 GB at 4-bit.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    11.4 GB
  • 8-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    7 GB
  • 4-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    4.9 GB
Your machine
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text / LLMVision-Language
10 versions — view changelog

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