📡 24/7 实时资讯

资讯广场

全球虚拟货币资讯·实时聚合

恐惧贪婪指数
65
贪婪 (+3)
BTC $72,134 +2.3%
ETH $3,892 +1.8%
SOL $168 +4.2%
17小时前 · Decrypt

Google Ships New Gemini Flash Models, But Pro Is Still Missing

Google launched <a href="https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-6-flash-3-5-flash-lite-3-5-flash-cyber/" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">three new AI models</a> today: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber. That wasn't what most people expected. After unveiling Gemini 3.5 Flash at <a href="https://decrypt.co/368393/google-unveils-gemini-omni-next-gen-ai-video-builder-simulate-world" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">Google I/O 2026</a> in May and promising a Pro version within a month, Google quietly missed its own deadline. Gemini 3.5 Pro was held back because it fell short of internal targets, <a href="https://www.bloomberg.com/news/articles/2026-07-16/google-gemini-launch-delayed-as-tech-falls-short-of-internal-goals" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">per <i>Bloomberg</i></a>, particularly on coding tasks. A late-June attempt to fix it by updating the training data—the massive datasets a model learns from—produced disappointing results. Alphabet stock fell roughly 4.4% on the report, erasing an estimated $200 billion in market cap in a single session. The last Pro-tier model Google shipped was <a href="https://decrypt.co/349087/google-releases-most-powerful-ai-model-gemini-3" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">Gemini 3</a>'s successor, Gemini 3.1 Pro, back in February. The Flash series is Google's line of speed-optimized models—fast, cost-effective, and built for AI agents, which are programs that operate semi-autonomously to handle tasks like managing documents, processing data pipelines, or browsing the web without a human clicking through each step. Pro models are the heavy lifters: slower, pricier, and built for complex reasoning where raw power matters more than speed. Gemini 3.6 Flash is the main release. It uses 17% fewer output tokens—tokens being the basic unit AI processes, roughly three-quarters of a word—than 3.5 Flash, per the Artificial Analysis Index. It's also cheaper: $1.50 per million input tokens and $7.50 per million output tokens, down from $9 on the output side for 3.5 Flash. For businesses running agents at scale, that difference compounds fast. On benchmarks—standardized tests that score AI by percentage of tasks completed correctly—3.6 Flash hit 49% on DeepSWE v1.1, which tests long-horizon software engineering like building and debugging full codebases, versus 37% for 3.5 Flash. On MLE-Bench, a machine learning engineering test, it scored 63.9% versus 49.7%. It topped the table on OSWorld-Verified—a test where the AI takes control of a computer screen to complete real tasks—at 83.0%, ahead of Claude Sonnet 5 (81.2%) and GPT-5.6 Luna (72.6%). Rivals in the same category still lead elsewhere: GPT-5.6 Luna scores 67% on DeepSWE and 84.7% on Terminal-Bench 2.1, which tests agentic terminal coding. Claude Sonnet 5 tops knowledge work on GDPval-AA v2—a bench

⚠️ 以上资讯仅供参考,不构成投资建议。数据来源于公开渠道,可能存在延迟。