## 🔍 Key Insights Alibaba officially open-sourced **Qwen3.5-397B-A17B**—the world's first **natively multimodal, sparse MoE architecture** open-source LLM, supporting **1M-token ultra-long context** and **4-bit local inference on consumer-grade hardware**. Concurrently, **Manus Agents** rolled out long-term memory and integrated toolchains on Telegram—signaling a new era for AI assistants: 'memorable and actionable.' ## 🚀 Major Updates - **Qwen3.5-397B-A17B officially open-sourced**: Alibaba released this 397B-parameter MoE model featuring native multimodal capabilities, empirically validated context length exceeding 262K tokens, and a hybrid linear attention architecture. - **Qwen3.5 gains full-stack inference ecosystem support**: Immediately integrated with **vLLM, SGLang, Ollama Cloud, and NVIDIA NIM/NeMo**, enabling plug-and-play deployment and fine-tuning. - **Unsloth AI enables consumer-grade local execution**: Delivers highly efficient 4-bit inference for Qwen3.5—enabling smooth operation of a hundred-billion-parameter multimodal model even on an RTX 4090. - **Manus Agents launches on Telegram**: Supports **long-term memory**, integrations with **Gmail and Notion**, and multimodal content generation—the first lightweight, actionable AI assistant deployed in production. - **Ant Group open-sources Ling-2.5-1T, a trillion-parameter model**: Features hybrid linear attention, supports **million-token long-text processing**, and delivers **millisecond-level real-time response**, expanding the frontier of inclusive intelligence. - **OneVision-Encoder introduces codec-aligned sparsity**: A new paper establishes this principle as a foundational paradigm for multimodal intelligence—potentially unifying vision-language representation learning pathways. - **GAPO algorithm solves RL programming noise challenges**: By leveraging HDI interval estimation and median-based advantage value modeling, GAPO significantly improves training robustness of code LLMs in complex, real-world contexts. - **Qwen3.5 demonstrates strong agent engineering capability**: Generated a *Stardew Valley*-style game in a single file—and autonomously debugged code, fixed issues, and submitted a Pull Request—validating end-to-end software engineering closure.