[whatmodel.sh](../../README.md) / Gemini 2.0 Flash-Lite Preview (02-05) # Gemini 2.0 Flash-Lite Preview (02-05) Google · released 2025-02 · closed weights **score 59.6** ±2.3 · 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 2.0 Flash-Lite Preview (02-05) among every model on that task or test, worst to best. 
task                vs the others          rank  counts  tests
chat & writing      ▁▁▁▃▅▄▇█●▇▇▃   #190 of 474*     57%      1
vision & documents  ▁▁▂▃▂▃●▄▆██▄   #129 of 189*     38%      1
chat & writing · #190 of 474 · 57% of its score Beats [MiniMax-M2](minimax-m2.md), [MiniCPM5 2B](minicpm5-2b.md), [Granite 4.2 30B](granite-4-2-30b.md) here, though they rank higher overall. Trails [LFM2.5 1.2B Thinking](lfm2-5-1-2b-thinking.md), [LFM2.5 8B-A1B](lfm2-5-8b-a1b.md), [LFM2.5 2.6B](lfm2-5-2-6b.md) here, though they rank lower overall. 
test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1353.5  ▁▁▁▂▃▃▃▆●▇█▃ beats 198/385  avg 1260       57%  blunt
vision & documents · #129 of 189 · 38% of its score Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md) here, though they rank higher overall. Trails [Llama 4 Maverick (402B-A17B)](llama-4-maverick.md), [Qwen3-VL 8B Thinking](qwen3-vl-8b-thinking.md), [Qwen3-VL 30B-A3B Instruct](qwen3-vl-30b-a3b-instruct.md) here, though they rank lower overall. 
test                             result  vs the others in its run   difficulty  counts  why
Arena vision (style controlled)  1135.8  ▁▁▂▂▂▂▃●▅▅█▇ beats 41/152  avg 1061       38%  blunt
other tests (1) 
test                                result  vs the others in its run    difficulty           counts  why
Vectara hallucination leaderboard…   98.8%  ▁▁▂▃▄▄█▆▃▂●▁ beats 135/140  very easy · avg 94%    2.3%  blunt · maxed out · noisy
## 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   95% ▇▇▇▇▇▇▇▇▇▇▇
Vectara hallucination leaderboard        1    2% ▇
prior: pull toward the middle                 2% ▇
weighted average                            = 59.6
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/gemini-2-0-flash-lite-preview-02-05) · [JSON](https://whatmodel.sh/api?format=json&all=1)