[whatmodel.sh](../../README.md) / Gemini 2.5 Flash Preview (09-2025) # Gemini 2.5 Flash Preview (09-2025) Google · released 2025-09 · closed weights **score 62.9** ±1.2 · comparison only: no current run option verified · from 7 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 Preview (09-2025) among every model on that task or test, worst to best. 
task                vs the others          rank  counts  tests
agent tasks         ▁▁▂▆█●▅▄▄▃▁▁    #192 of 354     26%      3
coding              ▁▁▁▃▄▆█●▅▄▃▁   #208 of 539*     50%      2
chat & writing      ▁▁▁▃▅▄▇█▇●▇▃   #130 of 474*     16%      1
vision & documents  ▁▁▂▃▂▃▅▄▆●█▄    #76 of 189*     11%      1
agent tasks · #192 of 354 · 26% of its score Beats [o1 (2024-12-17)](o1-2024-12-17.md), [o3-mini](o3-mini.md), [DeepSeek R1 0528](deepseek-r1-0528.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Mini](jamba-1-5-mini.md), [Jamba 1.5 Large](jamba-1-5-large.md) here, though they rank lower overall. 
test                result  vs the others in its run  difficulty           counts  why
τ²-bench Retail      61.7%  █●··▄··▄·▄·▄ beats 2/6    medium · avg 36%        10%  at its level
SWE-bench Verified   34.2%  █·█●·······█ beats 4/6    very hard · avg 10%    8.1%  sharp · at its level
τ²-bench Airline     56.7%  ▄▄······●█▄▄ beats 2/6    hard · avg 28%         7.8%  at its level
coding · #208 of 539 · 50% of its score Trails [QwQ-32B-Preview](qwq-32b-preview.md), [Ministral 3 8B Reasoning 2512](ministral-3-8b-reasoning.md), [Phi-4-reasoning 14B](phi-4-reasoning.md) here, though they rank lower overall. 
test                                result  vs the others in its run  difficulty            counts  why
Aider polyglot (225 exercises, tw…   40.0%  ●▄····▄··█·▄ beats 1/6    very hard · avg 7.3%     42%  sharp · at its level
SWE-bench Verified                   34.2%  █·█●·······█ beats 4/6    very hard · avg 10%     8.1%  sharp · at its level
chat & writing · #130 of 474 · 16% of its score Beats [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [GPT-5.4 nano](gpt-5-4-nano.md), [Step 3.5 Flash (196B-A11B)](step-3-5-flash.md) here, though they rank higher overall. Trails [Nemotron-Cascade-8B](nemotron-cascade-8b.md), [Mistral Large 3 (675B-A41B)](mistral-large-3.md), [Gemini 2.5 Flash](gemini-2-5-flash.md) here, though they rank lower overall. 
test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1403.0  ▁▁▁▂▃▃▃▆▆●█▃ beats 249/385  avg 1260       16%  blunt
vision & documents · #76 of 189 · 11% of its score Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5](gpt-5.md), [o3](o3.md) here, though they rank higher overall. 
test                             result  vs the others in its run   difficulty  counts  why
Arena vision (style controlled)  1229.8  ▁▁▂▂▂▂▃▄▅●█▇ beats 89/152  avg 1061       11%  blunt
other tests (1) 
test                                result  vs the others in its run  difficulty      counts  why
Multi-IF (aggregation unspecified)   82.5%  ▄·····●█▄▄·▄ beats 1/6    easy · avg 66%    3.9%  typical
## 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
ServiceNow-AI/Apriel-1.6-15b-Thinker mo…        5   72% ▇▇▇▇▇▇▇▇▇
LMArena leaderboard dataset                     2   27% ▇▇▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 62.9
Licences: ServiceNow-AI/Apriel-1.6-15b-Thinker model card ([MIT](../../licenses/cards-final-NOTICE.txt)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/gemini-2-5-flash-preview-09-2025) · [JSON](https://whatmodel.sh/api?format=json&all=1)