[whatmodel.sh](../../README.md) / Gemini 2.5 Flash-Lite Preview (06-17) # Gemini 2.5 Flash-Lite Preview (06-17) Google · released 2025-06 · closed weights **score 61.5** ±2.2 · comparison only: no current run option verified · from 3 benchmark results across 2 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks Gemini 2.5 Flash-Lite Preview (06-17) among every model on that task or test, worst to best.}

task                vs the others          rank  counts  tests
agent tasks         ▁▁▂●█▄▅▄▄▃▁▁   #280 of 354*     12%      1
chat & writing      ▁▁▁▃▅▄▇█●▇▇▃   #161 of 474*     52%      1
vision & documents  ▁▁▂▃▂▃▅▄●██▄   #104 of 189*     34%      1

agent tasks · #280 of 354 · 12% of its score

Beats [o3-mini](o3-mini.md) here, though they rank higher overall. Trails [Granite 4.0 1B](granite-4-0-1b.md), [SmolLM3 3B](smollm3-3b.md), [Phi-3.5-mini-instruct](phi-3-5-mini-instruct.md) here, though they rank lower overall.

test                                result  vs the others in its run  difficulty      counts  why
BFCL V4 (2025-11-03 archive, mode…   35.3%  ▃··●▃▃·▅·▃·█ beats 2/10   hard · avg 33%     12%  at its level

chat & writing · #161 of 474 · 52% of its score

Beats [o3-mini](o3-mini.md), [INTELLECT-3](intellect-3.md), [MiniMax-M2](minimax-m2.md) here, though they rank higher overall. Trails [LFM2.5 8B-A1B](lfm2-5-8b-a1b.md), [LFM2.5 2.6B](lfm2-5-2-6b.md), [Nemotron-Cascade-8B](nemotron-cascade-8b.md) here, though they rank lower overall.

test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1374.9  ▁▁▁▂▃▃▃▆●▇█▃ beats 218/385  avg 1260       52%  blunt

vision & documents · #104 of 189 · 34% of its score

Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5 mini](gpt-5-mini.md), [GLM-4.6V](glm-4-6v.md) here, though they rank higher overall. Trails [Qwen3.5 4B](qwen3-5-4b.md), [GPT-4.1 mini](gpt-4-1-mini.md) here, though they rank lower overall.

test                             result  vs the others in its run   difficulty  counts  why
Arena vision (style controlled)  1188.4  ▁▁▂▂▂▂▃▄●▅█▇ beats 65/152  avg 1061       34%  blunt

## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md)

source                                    results  share of the score
LMArena leaderboard dataset                     2   86% ▇▇▇▇▇▇▇▇▇▇
Berkeley Function Calling Leaderboard r…        1   12% ▇
prior: pull toward the middle                        2% ▇
weighted average                                   = 61.5

_{Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Berkeley Function Calling Leaderboard result archive ([Apache-2.0](../../licenses/bfcl-result-archive-v4-Apache-2.0.txt))} ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/gemini-2-5-flash-lite-preview-06-17) · [JSON](https://whatmodel.sh/api?format=json&all=1)