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Public story · 2026-02-16 · source-backed
Beyond the model itself (covered in Breaking News), the Qwen-Agent framework shipping alongside Qwen 3.5 includes built-in planning, tool orchestration, and memory management. It's a complete agent development stack, not just a model. GitHub
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Qwen 3.5 is the first major model pretrained specifically for agentic multimodal workflows from the first training stage, not fine-tuned after the fact. 397B total / 17B active parameters (MoE architecture), 256K context window, 201 languages. Ships with Qwen Code (terminal ag...
Alibaba released Qwen3.6-27B on April 22. Dense architecture. Open weights. 77.2% on SWE-bench Verified, within 3.7 points of Claude Opus 4.6. On SkillsBench, it scores 48.2% versus its own 397B MoE predecessor's 30.0%. That's a 77% improvement with 14.8x fewer parameters. Let...
Terminal-based coding agent powered by Qwen 3.5. Ships with Qwen-Agent framework and Qwen3-Coder (code-specialized model). Build agentic applications using a completely open-weight stack. GitHub ---
A spec is a press release until someone who didn't write it implements it. GitHub made Agent Plugins 1.0 generally available on August 12 across VS Code, Copilot CLI, the Copilot SDK, and the Copilot app on all plans. The spec, published August 6, was co-authored by AWS, Anysp...
Moonshot AI dropped Kimi K2.6 today and the numbers are hard to ignore. One trillion parameters total, 32 billion active per token across 384 experts, 256K context window, and native multimodal input. It scores 58.6 on SWE-Bench Pro versus GPT-5.4's 57.7 and Claude Opus 4.6's...
Qwen released Qwen-AgentWorld-35B-A3B on June 24: 35B total parameters, 3B active in an MoE, 256K context, Apache 2.0. It ships with AgentWorldBench. (GitHub) The idea is the interesting part. It's a "language world model," trained to simulate the environment an agent acts in....
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