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@berryxia· @berryxia · X·· 2026-05-20精选AI 评分79
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Google DeepMind 发布 Gemini 3.5 Flash,Artificial Analysis 预发布测试显示其 Intelligence Index 得 55 分,比 Gemini 3 Flash 高 9 分。

推荐理由

借 Artificial Analysis 的预发布基准,可以看到 Gemini 3.5 Flash 在智能与速度上的提升及其成本代价。

正文

兄弟们,Google DeepMind刚放出的Gemini 3.5 Flash,直接把Intelligence vs Speed的Pareto前沿拉新高度了。

Artificial Analysis拿到预发布权限,测完后结论很明确:

它在Intelligence Index拿到55分,比Gemini 3 Flash高9分,直接超过Grok 4.3和Claude Sonnet 4.6。

Agentic任务(GDPval-AA)Elo评分飙到1656,远超前代。

幻觉率从92%暴降到61%。

多模态理解也继续领跑,MMMU-Pro 84%。

输出速度超280 tokens/s,比上一代快70%。

看起来几乎完美。

但代价是:跑一次Artificial Analysis Intelligence Index的成本是Gemini 3 Flash的5.5倍,比Gemini 3.1 Pro贵75%。

定价直接3倍($1.5/$9 per 1M input/output),加上agentic任务里token用量显著增加。

速度和智能终于兼得,但价格直接把“Flash”这个词的便宜属性干掉了。

完整基准在这里:artificialanalysis.ai/models…

引用Artificial Analysis (@ArtificialAnlys)@ArtificialAnlys
Google’s new Gemini 3.5 Flash is the clear leader on the Intelligence vs Speed Pareto frontier and makes large gains on GDPval-AA (real-world agentic tasks), but is 5x the cost of Gemini 3 Flash @GoogleDeepMind gave us pre-release access to Gemini 3.5 Flash, the latest model in its Flash family, which has traditionally has offered faster, lower-cost alternatives to Gemini Pro models. Gemini 3.5 Flash scores 55 on the Artificial Analysis Intelligence Index, up 9 points from Gemini 3 Flash, driven primarily by agentic performance gains and hallucination reduction. It achieves speeds of over 280 output tokens/s, but higher token usage and token pricing make it over 5x more costly to run the Intelligence Index than Gemini 3 Flash, and 75% more costly than Gemini 3.1 Pro. Gemini 3.5 Flash is $1.50/1M input and $9/1M output tokens, Gemini 3 Flash was $0.5/$3 per 1M input/output tokens, a 3x increase. The rest of the increase was driven by higher token usage when running our benchmarks Key results for Gemini 3.5 Flash with ‘high’ thinking level: ➤ 9 point Intelligence Index improvement: Gemini 3.5 Flash scores 55 on the Artificial Analysis Intelligence Index, up 9 points from Gemini 3 Flash. This places it ahead of Grok 4.3 (high, 53) and Claude Sonnet 4.6 (max, 52). The model improves across nearly all evaluations, with the largest gains coming from agentic evaluations and AA-Omniscience (knowledge and hallucination). On AA-Omniscience, Gemini 3.5 Flash improves by 11 points, driven primarily by reduced hallucinations, with its hallucination rate falling to 61%, a 31 point decrease compared to Gemini 3 Flash ➤ Agentic capability improvements: Gemini 3.5 Flash improves substantially over Gemini 3 Flash across our agentic evaluations, in both GDPval-AA (real-world agentic tasks) and Tau2-Bench Telecom (agentic tool use). Its GDPval-AA result is especially notable, achieving an Elo of 1656, well ahead of Gemini 3 Flash (1204) and Gemini 3.1 Pro (1314), and just behind GPT-5.4 (xhigh, 1674). This represents a meaningful step forward for Google in agentic performance, which has historically been a relative weakness for Gemini models ➤ Speed-intelligence frontier: Gemini 3.5 Flash achieves speeds of over 280 output tokens per second, ~70% faster than Gemini 3 Flash and models such as gpt-oss-120b and GPT-5.4 mini (xhigh). With its 55 Intelligence Index score, this places Gemini 3.5 Flash on the speed-intelligence Pareto frontier alongside Gemini 3.1 Pro and Gemini 3.1 Flash-Lite, reinforcing Google’s strength in models balancing speed and intelligence ➤ 5.5x increase in cost to run: Gemini 3.5 Flash costs $1,552 to run the Artificial Analysis Intelligence Index, 5.5x more than Gemini 3 Flash and 75% more than Gemini 3.1 Pro. This is driven by increases in both token usage and token prices. Output token usage is broadly unchanged from Gemini 3 Flash (73M vs. 72M), but input token usage increases significantly, driven primarily by an increase in the number of turns in agentic evaluations. Gemini 3.5 Flash is priced 3x higher than Gemini 3 Flash at $1.50/$9.00 per 1M input/output tokens, with a 90% discount for cached input tokens ➤ Google continues to lead multimodal performance: Gemini 3.5 Flash is multimodal, supporting image, video, and speech input alongside text. This differs from many proprietary models, including Claude Opus 4.7, Grok 4.3, and GPT-5.5, which support image input only. In our multimodal evaluation, MMMU-Pro, Gemini 3.5 Flash scores 84% - the highest score recorded. This puts models from Google in the top two spots, with Gemini 3.1 Pro scoring 82% Key model details: ➤ Context window: Retains the same 1M context window as Gemini 3 Flash ➤ Multimodality: Text, image, video and speech input with text output only ➤ Pricing: $1.50/$9.00 per million input/output tokens, with a 90% discount for cached input tokens Congratulations @GoogleDeepMind , @sundarpichai and @demishassabis on the great release!
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来源:@berryxia · x.com