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Google DeepMind·· 2026-03-04精选AI 评分70

Gemini 3.1 Flash-Lite 发布:主打大规模低成本智能

Gemini 3.1 Flash-Lite: Built for intelligence at scale

AI 导读

Google DeepMind 发布 Gemini 3.1 Flash-Lite,这是 Gemini 3 系列中最快且最具成本效益的模型。该模型已通过 Google AI Studio 和 Vertex AI 推出预览版,输入 token 价格为 $0.25/1M,输出为 $1.50/1M。

推荐理由

官方给出其相对 2.5 Flash 的速度提升与 token 定价,读者可据此评估高频工作流的成本变化。

正文

Mar 03, 2026

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Today, we're introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier.

Starting today, 3.1 Flash-Lite is rolling out in preview to developers via the Gemini API in Google AI Studio and for enterprises via Vertex AI.

Cost-efficiency without compromise

Priced at just $0.25/1M input tokens and $1.50/1M output tokens, 3.1 Flash-Lite delivers enhanced performance at a fraction of the cost of larger models. It outperforms 2.5 Flash with a 2.5X faster Time to First Answer Token and 45% increase in output speed, according to the Artificial Analysis benchmark while maintaining similar or better quality. This low latency is needed for high-frequency workflows, making it an ideal model for developers to build responsive, real-time experiences.

The image shows two bar charts titled "Speed & Cost Efficiency," comparing the "Output speed (higher is better)" and "Price (lower is better)" of Gemini 3.1 Flash-Lite against several other models, including Gemini 2.5 Flash-Lite, GPT-5 mini, Claude 4.5 Haiku, and Grok 4.1 Fast.

Gemini 3.1 Flash-Lite outperforms 2.5 Flash in speed and quality.

3.1 Flash-Lite achieves an impressive Elo score of 1432 on the Arena.ai Leaderboard and outperforms other models of similar tier across reasoning and multimodal understanding benchmarks, including 86.9% on GPQA Diamond and 76.8% on MMMU Pro–even surpassing larger Gemini models from prior generations like 2.5 Flash.

The image displays a comparison table of several AI models, including "Gemini 3.1 Flash-Lite," "Gemini 2.5 Dynamic," "Gemini 2.5 Flash-Lite," "GPT-5 mini," "Claude 4.5 Haiku," and "Grok 4.1 Fast," across various metrics such as input/output price, output speed, and different academic, reasoning, and factual benchmarks.

Adaptive intelligence at scale for developers

Beyond its raw performance, Gemini 3.1 Flash-Lite comes standard with thinking levels in AI Studio and Vertex AI, giving developers the control and flexibility to select how much the model “thinks” for a task, which is critical for managing high-frequency workloads. 3.1 Flash-Lite can tackle tasks at scale, like high-volume translation and content moderation, where cost is a priority. And it can also handle more complex workloads where more in-depth reasoning is needed, like generating user interfaces and dashboards, creating simulations or following instructions.

Early-access developers on AI Studio and Vertex AI, and companies like Latitude, Cartwheel and Whering are already using 3.1 Flash-Lite to solve complex problems at scale. Early testers highlighted 3.1 Flash-Lite’s efficiency and reasoning capabilities, saying it can handle complex inputs with the precision of a larger-tier model, plus follow instructions and maintain adherence.

Quote from Kolby Nottingham at Latitude regarding the instruction-following capabilities and speed of Google's model.

Quote from Andrew Carr at Cartwheel highlighting the speed and multimodal labeling capabilities of 3.1 Flash-Lite.2

Quote from Bianca Rangecroft at Whering about using 3.1 Flash-Lite for consistent item tagging and data labeling

Quote from Kaan Ortabas at HubX detailing the performance metrics and cost efficiency of Gemini 3.1 Flash-Lite.

We look forward to seeing what you build with 3.1 Flash-Lite and the rest of the Gemini 3 series models.

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来源:Google DeepMind · deepmind.google