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Model catalogGemini 2.5 Flash-Lite-Preview-09-2025
GE

Gemini 2.5 Flash-Lite-Preview-09-2025

聊天大模型

Gemini 2.5 Flash-Lite-Preview-09-2025

Release date: 2025-09-25更新于: 2025-09-26 07:35:34457
Live demoGitHubHugging FaceCompare
Parameters
Not disclosed
Context length
1000K
Chinese support
Supported
Reasoning ability

Gemini 2.5 Flash-Lite-Preview-09-2025 is an AI model published by Google Deep Mind, released on 2025-09-25, for 聊天大模型, with 0.0B parameters, and 1000K tokens context length, under the 不开源 license.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

Gemini 2.5 Flash-Lite-Preview-09-2025

Model basics

Reasoning traces
Supported
Thinking modes
Thinking modes not supported
Context length
1000K tokens
Max output length
65536 tokens
Model type
聊天大模型
Release date
2025-09-25
Model file size
No data
MoE architecture
No
Total params / Active params
0.0B / N/A
Knowledge cutoff
No data
Gemini 2.5 Flash-Lite-Preview-09-2025

Open source & experience

Code license
不开源
Weights license
不开源- 不开源
GitHub repo
GitHub link unavailable
Hugging Face
Hugging Face link unavailable
Live demo
https://aistudio.google.com/
Gemini 2.5 Flash-Lite-Preview-09-2025

Official resources

Paper
Continuing to bring you our latest models, with an improved Gemini 2.5 Flash and Flash-Lite release
DataLearnerAI blog
No blog post yet
Gemini 2.5 Flash-Lite-Preview-09-2025

API details

API speed
3/5
💡Default unit: $/1M tokens. If vendors use other units, follow their published pricing.
Standard pricingStandard
ModalityInputOutput
Text$0.1$0.4
Image$0.1--
Gemini 2.5 Flash-Lite-Preview-09-2025

Benchmark Results

Gemini 2.5 Flash-Lite-Preview-09-2025 currently shows benchmark results led by MMMU (20 / 28, score 72.70), DocVQA (4 / 5, score 92), LiveBench (47 / 52, score 58.46). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking
All modesNormalThinking
Thinking mode details (1)
All thinking modesDefault (Thinking Mode)

综合评估

1 evaluations
Benchmark / mode
Score
Rank/total
LiveBench
Thinking Mode
58.46
47 / 52
View benchmark analysisCompare with other models
Gemini 2.5 Flash-Lite-Preview-09-2025

Publisher

Google Deep Mind
Google Deep Mind
View publisher details
Gemini 2.5 Flash-Lite-Preview-09-2025

Model Overview

Gemini 2.5 Flash-Lite-Preview-09-2025 是 Gemini 模型家族中专注于超低延迟、高并发和最高性价比的一个子模型。它是为那些对延迟和成本有极其严格要求的任务而设计。

定位与特点

Flash-Lite 版本是在保持 Gemini 2.5 Flash 核心能力的基础上,通过进一步的优化来追求极致的效率,其核心定位是:

  1. 超低延迟: 它针对需要快速响应的应用场景进行了优化,能提供 Gemini 模型家族中最快的响应速度。
  2. 最高效率/性价比: 在成本控制方面表现出色,使其成为大规模、高并发部署的首选。
  3. 核心智能保持: 尽管追求效率,但它依然保持了进行推理、编码、函数调用和搜索增强等核心任务的能力。

主要改进亮点(针对 09-2025 预览版)

与 Gemini 2.5 Flash 09-2025 的更新类似,Flash-Lite 预览版也在效率方面进行了加强:

  • 更高的 Token 效率: 模型在开启“思考(Thinking)”功能时,能以更少的 Token 完成任务,进一步降低延迟和运行成本。
  • 持续的 Agentic 能力支持: 尽管它是“Lite”版本,但仍然支持工具调用(Tool Use)和 Agentic 工作流,使其适用于需要快速集成外部功能的轻量级智能体应用。

应用场景

Gemini 2.5 Flash-Lite 适用于以下需要“速度优先”的场景:

类别典型应用
实时交互快速响应的聊天机器人、客户服务系统中的即时回复。
大规模数据处理需要在极短时间内对海量数据进行分类、过滤或标签化的任务。
高并发 API 调用网站或应用后端对模型的 API 调用频率极高,对每秒事务数(TPS)要求严格。
轻量级智能体需要快速使用 Function Calling(函数调用)来执行简单但关键操作的 Agentic 任务。

如何使用

  • 预览模型 ID: 开发者可以使用 gemini-2.5-flash-lite-preview-09-2025 模型字符串在 Google AI Studio 和 Vertex AI 上进行测试。
  • 最新版本别名: Google 也为它推出了 -latest 别名 (gemini-flash-lite-latest),始终指向该系列最新的优化版本,方便开发者持续进行试验。

简而言之,Gemini 2.5 Flash-Lite 是为追求极致速度和最低成本的开发者提供的版本,它在效率上做到了最优,同时保持了执行核心智能任务的能力。

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