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Gemini 2.5 Flash-Lite (Non-reasoning)

GoogleGemini開源權重Creative Commons Attribution 4.0 License

描述

Gemini 2.5 Flash-Lite is a model developed by Google DeepMind, designed to handle various tasks including reasoning, science, mathematics, code generation, and more. It features advanced capabilities in multilingual performance and long context understanding. It is optimized for low latency use cases, supporting multimodal input with a 1 million-token context length.

發布日期
2025-06-17
參數規模
—
上下文長度
1.0M
支援模態
audio, image, pdf, text, video

能力雷達圖

26
general
35
coding
49
reasoning
28
science
45
agents
88
multimodal

排行榜排名

領域#排名分數來源
音訊能力36
64.0
AA
程式碼能力榜365
28.0
AA
通用能力榜444
29.0
AA
科學能力468
26.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)64.6%自報

Code

LiveCodeBench33.7%自報
SWE-Bench Verified31.6%自報
Aider-Polyglot26.7%自報

Factuality

FACTS Grounding84.1%自報
SimpleQA10.7%自報

General

Global-MMLU-Lite81.1%自報
MMMU72.9%自報
Vibe-Eval51.3%自報
MRCR v216.6%自報
Arc2.5%自報

Math

AIME 202549.8%自報
Humanity's Last Exam5.1%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
35.3
Intelligence Index(Artificial Analysis)
6.7
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Aime(MAA (Mathematical Association of America))
0.5
Gpqa(NYU + Cohere + Anthropic (2023))
0.5
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.4
Aime 25(MAA (Mathematical Association of America))
0.4
Lcr(Artificial Analysis)
0.3
Ifbench(Google Research (2023))
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Scicode(UIUC + Argonne National Lab (2024))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))
Language
80
Grounding
80
Healthcare
70
Multimodal
60
Physics
60
Biology
60
Chemistry
60
Reasoning
50
Factuality
50
General
40
Vision
40
Math
30
Frontend Development
30
Code
30
Long Context
20

定價

輸入價格$0.1 / 1M tokens
輸出價格$0.4 / 1M tokens
混合價格(3:1)$0.175 / 1M tokens
快取讀取價格$0.01 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

1 個供應商

供應商輸入輸出
1Google主要
$0.1
$0.4

比較該模型在不同 API 供應商之間的定價。

外部連結

LLM StatsArtificial Analysis