## 🔍 Key Insights **The Qwen 3.5 series** has powerfully ignited the open-source large language model (LLM) ecosystem. Its **397B parameters**, **native multimodality**, and **MoE + Linear Attention architecture** received full-stack Day-One support from NVIDIA, AMD, Ollama, ZenMux, LMSYS, and mlx-vlm. Meanwhile, **LlamaIndex** is rapidly evolving into foundational AI Agent infrastructure—replacing its subscription model with the **$LLAMA token**, and significantly upgrading its **PDF → Markdown/JSON parsing capability**, thereby reinforcing the 'cognitive infrastructure' underpinning intelligent agents. ## 🚀 Top Highlights - **Qwen 3.5-397B-A17B launches on LMSYS Arena**: Alibaba's new natively multimodal open model is now live on LMSYS Arena, supporting benchmarking across three modalities: text, vision, and code. - **NVIDIA and AMD jointly announce Day-One support for Qwen 3.5**: Both companies offer free APIs—NVIDIA via NeMo, AMD via SGLang/vLLM—and hardware acceleration on their respective Instinct GPUs. - **Ollama Cloud and ZenMux roll out Qwen 3.5**: Ollama Cloud enables plug-and-play inference; ZenMux debuts **Qwen 3.5 Plus**, featuring a novel **Gated DeltaNet + Sparse MoE** architecture. - **mlx-vlm v0.3.12 adds native macOS support**: For the first time, the Qwen 3.5 series now supports on-device visual-language model inference on Apple Silicon Macs. - **LlamaCloud launches an enhanced PDF parsing engine**: Capable of high-fidelity extraction from complex PDFs—including tables and charts—with structured output in Markdown or JSON. - **LlamaIndex adopts the $LLAMA token for unified API billing**: Moving away from monthly subscriptions, it introduces a universal token-based pricing model tailored for agent-driven API calls. - **Google Antigravity releases a visual UI editor for building Agents**: Users simply screenshot a UI region and issue natural-language instructions to instantly reconstruct frontend interfaces in real time. - **Fu Sheng publicly releases the OpenClaw open-source framework**, demonstrating personalized Lunar New Year greetings for **611 job-specific roles**: All generated in just four minutes—validating the 'individual-as-a-team' productivity paradigm enabled by AI assistants.