On October 20, Synaptics launched the Astra SR200 series of three processors integrating Google's open-source Coral NPU technology, targeting smart glasses, cameras, industrial sensors and other devices. The two companies also announced expanded availability of the Coralboard platform, supporting local execution of models such as Google's Gemma.
SiFive and AMD jointly demonstrated at the AI Infra Summit a RISC-V processor plus AMD Radeon AI PRO R9700 system running Google Gemma4-E2B via ROCm 10.0, aiming to combine open-source software with RISC-V's open architecture for next-generation data center AI computing. The companies will continue evaluating ROCm optimizations for RISC-V-based servers to improve processing speed and support larger models.
谷歌于2026年6月发布开源语言模型DiffusionGemma，首次将图像AI扩散机制引入文本生成，打破传统逐字自回归范式。该模型从随机噪声迭代优化，并行输出256个词块。经英伟达优化，在单GPU单用户模式下，运行速度比同类传统模型快近四倍，如H100显卡处理单请求时表现显著提升。
谷歌于6月10日发布开源实验模型DiffusionGemma，采用文本扩散架构，在专用GPU上文本生成速度较传统自回归模型最高提升4倍，旨在提升AI生成效率，但官方对此保持谨慎态度。
<body><div>Google releases a new multimodal model Gemma 4 12B, revolutionizing the traditional architecture by eliminating the separate encoder component, achieving effici</div></body>
**Google DeepMind Launches Gemma4: A New Era of Open-Source AI** Google DeepMind has officially unveiled the Gemma4 open-source model series, marking a significant annual update. This release represents a generational leap in performance and a major shift in open-source policy. Google has transitioned the model's license to the globally permissive Apache 2.0, granting developers greater freedom for commercial use and modification. **Complete Model Spectrum: The "Four Pillars"** The Gemma4 series introduces four distinct models for comprehensive scenario coverage: * **31B Dense (Flagship):** Featuring 310 billion activated parameters and 256K context length, it ranks #3 on the Arena AI leaderboard and runs on a single H100 GPU. * **26B A4B MoE (Value Leader):** Utilizing a Mixture-of-Experts architecture (252B total, 38B active parameters), it offers inference speed near a 4B model with superior quality, ranking #6. * **E4B & E2B (Edge-Optimized):** Designed for mobile and embedded devices. Using Per-Layer Embeddings, their effective parameters are compressed to 4.5B and 2.3B respectively, with E2B requiring under 1.5GB memory on some devices. **Performance Breakthroughs: A Generational Leap** Gemma4 demonstrates dramatic improvements over its predecessor, Gemma327B: * **Mathematics:** AIME2026 score surged from 20.8% to 89.2%. * **Coding:** Codeforces ELO rose from 110 to 2150; LiveCodeBench performance increased from 29.1% to 80.0%, establishing it as a top open-source coding assistant. * **Reasoning:** GPQA Diamond score nearly doubled from 42.4% to 84.3%. * **Multilingual:** Natively supports 140+ languages, achieving an 88.4% MMMLU score. **Core Innovations: "Thinking Mode" and Agent Capabilities** Beyond scaling, Gemma4 incorporates advanced interactive features: * **Thinking Mode:** A toggleable feature enabling internal reasoning before output, significantly improving accuracy in multi-step planning tasks. * **Native Agent Support:** Supports function calling and structured JSON output. Google released an open-source Agent Development Kit (ADK) to empower
Google DeepMind hints at releasing Gemma 4, a new open-source model with 120B parameters, aiming to challenge local deployment limits and regain dominance in th