Alibaba releases Qwen3.5-35B-A3B, a 35B multimodal model with Apache 2.0 license
Alibaba's Qwen team has released Qwen3.5-35B-A3B-Base, a 35-billion parameter multimodal model supporting image-text-to-text tasks. The model is available under the Apache 2.0 license and compatible with major inference endpoints including Azure deployment.
Qwen3.5-35B-A3B-Base — Quick Specs
Alibaba's Qwen division has released Qwen3.5-35B-A3B-Base, a 35-billion parameter multimodal language model designed for image-text-to-text tasks.
Model Details
The model was published on February 24, 2026 on Hugging Face and carries an Apache 2.0 license, allowing both commercial and research use without licensing restrictions. It is tagged as part of the Qwen3.5 MoE (mixture of experts) family, indicating the model uses conditional computation techniques to improve efficiency.
Qwen3.5-35B-A3B-Base supports multimodal inputs, processing both images and text to generate text outputs. The model is compatible with the Transformers library and uses SafeTensors format for weight storage, a security-focused serialization standard.
Availability and Deployment
The model has achieved 1,937 downloads and 62 likes on Hugging Face as of publication. It is compatible with inference endpoints through major cloud providers, including Azure deployment options, making it accessible for production use cases.
The base model variant indicates this is the foundational version without instruction-tuning or fine-tuning for specific tasks, leaving optimization to end users or downstream applications.
Context
This release continues Alibaba's Qwen series momentum in the open-weight model space. The Qwen3.5 line represents an iteration beyond Qwen3, with the A3B variant designation referring to a specific model configuration within the 35B parameter class.
The mixture-of-experts architecture employed in this model typically provides efficiency improvements during inference compared to dense models of equivalent parameter count, though exact computational requirements are not yet published.
What This Means
Alibaba is positioning Qwen3.5-35B-A3B as an open alternative for organizations needing multimodal capabilities at the 35B scale. The Apache 2.0 license removes commercial deployment barriers, and cloud provider integration lowers infrastructure barriers. The model joins a competitive field of open multimodal 30B+ parameter models from Meta, Mistral, and others, each with different architectural choices and trade-offs in performance, efficiency, and licensing.
Related Articles
Moonshot AI Releases Kimi K2.6: 1T-Parameter MoE Model with 256K Context and Agent Swarm Capabilities
Moonshot AI has released Kimi K2.6, an open-source multimodal model with 1 trillion total parameters (32B activated) and 256K context window. The model achieves 80.2% on SWE-Bench Verified, 58.6% on SWE-Bench Pro, and supports horizontal scaling to 300 sub-agents executing 4,000 coordinated steps.
Alibaba Qwen Releases 35B Parameter Qwen3.6-35B-A3B Model with 262K Native Context Window
Alibaba Qwen has released Qwen3.6-35B-A3B, a 35-billion parameter mixture-of-experts model with 3 billion activated parameters and a 262,144-token native context window extendable to 1,010,000 tokens. The model scores 73.4 on SWE-bench Verified and features FP8 quantization with performance metrics nearly identical to the original model.
Alibaba Releases Qwen3.6-35B-A3B: 35B Parameter MoE Model with 262K Context Window
Alibaba has released Qwen3.6-35B-A3B, the first open-weight model in the Qwen3.6 series. The model features 35B total parameters with 3B activated, a native 262K context window extensible to 1.01M tokens, and achieves 73.4% on SWE-bench Verified using 256 experts with 8 activated per token.
Tencent Releases HY-World 2.0: Open-Source Multi-Modal Model Generates 3D Worlds from Text and Images
Tencent has released HY-World 2.0, an open-source multi-modal world model that generates navigable 3D environments from text prompts, single images, multi-view images, or video. The model produces editable 3D assets including meshes and 3D Gaussian Splattings that can be directly imported into game engines like Unity and Unreal Engine.
Comments
Loading...