Alibaba Open-sources Qwen3.6-35B-A3B; Wan2.7 Tops Design Arena

This week, Alibaba open-sourced Qwen3.6-35B-A3B, a sparse Mixture of Experts (MoE) model that delivers strong performance in agentic coding and complex reasoning following the launch of Qwen3.

This week, Alibaba open-sourced Qwen3.6-35B-A3B, a sparse Mixture of Experts (MoE) model that delivers strong performance in agentic coding and complex reasoning following the launch of Qwen3.6-Plus. Meanwhile, Alibaba’s latest visual generation model Wan2.7 topped the Design Arena rankings in the video-to-video category, rivaling with top video generation models on the global crowdsourced benchmark for AI-generated design.

Alibaba Open-Sources Latest Qwen3.6 Model

Following the launch of Qwen3.6-Plus, Alibaba has open-sourced Qwen3.6-35B-A3B, a sparse Mixture-of-Experts (MoE) model featuring 35 billion total parameters with only 3 billion active during inference. Beyond its exceptional efficiency, the model delivers outstanding performance in agentic coding and complex reasoning, rivalling much larger dense models such as Gemma-31B.

In agentic coding area, Qwen3.6-35B-A3B showcases exceptionally powerful capabilities with minimal computational cost, making it a highly efficient coding assistant. On authoritative benchmarks – including Terminal-Bench 2.0 (evaluating terminal-based programming), NL2Repo (assessing long-horizon programming tasks), and QwenClawBench (an internal benchmark reflecting real-user distribution for Claw-agent capabilities)—the model significantly outperforms its predecessor, Qwen3.5-35B-A3B, and it is competitive with open-source models such as Gemma4-26B-A4B and Gemma4-31B.

The model also integrates seamlessly with popular third-party coding assistants, such as OpenClaw, Claude Code, and Qwen Code, to streamline development workflows and enable efficient, context-aware coding experiences.

As a multimodal foundation model, Qwen3.6-35B-A3B also exhibits robust perceptual understanding and advanced multimodal reasoning capabilities. Despite activating just 3 billion parameters, it is competitive with frontier models—including GPT-5-mini and Claude-Sonnet-4.5—across major vision-language benchmarks. Notably, the model demonstrates exceptional strength in spatial intelligence, significantly outperforming even the substantially larger Qwen3-VL-235B-A22B on several key tasks.

Qwen3.6-35B-A3B is now available with open weights on Hugging Face and ModelScope. It can also be accessed via API through Alibaba Cloud Model Studio under the identifier qwen3.6-flash, or tried instantly via Qwen Studio.

As a fully open-source, unified checkpoint, Qwen3.6-35B-A3B establishes a new benchmark for capability and efficiency at its scale. Since 2023, Alibaba has open-sourced more than 400 Qwen models. The Qwen family has achieved significant global adoption, with over 1 billion downloads and more than 200,000 derivative models created by developers worldwide. Alibaba remains committed to expanding the Qwen3.6 open-source family and pushing the boundaries of what efficient, accessible AI models can achieve.

Alibaba’s Wan2.7 Tops Design Arena Rankings

Alibaba’s visual generation model Wan2.7 has topped the Design Arena rankings in the video to video arena. Wan2.7-Video was unveiled in earlier April, it features four models including Text-to-Video model Wan2.7-t2v, Image-to-Video Wan2.7-i2v, Reference-to-Video Wan2.7-r2v, and Video Editing Wan2.7-videoedit. It unifies text, image, video, and audio inputs into a single cohesive system covering generation, editing, replication, reshaping, continuation, and referencing.

Design Arena is the world’s first crowdsourced benchmark for AI-generated design. It is powered by millions of votes from users in more than 190 countries.

This article was originally published on Alizila written by Crystal Liu and Shao Xiaoyi.

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Alibaba Open-sources Qwen3.6-35B-A3B; Wan2.7 Tops Design Arena

Alibaba Open-Sources Latest Qwen3.6 Model

Alibaba’s Wan2.7 Tops Design Arena Rankings

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