[whatmodel.sh](../../README.md) / Gemini 2.0 Pro Experimental (02-05) # Gemini 2.0 Pro Experimental (02-05) Google · released 2025-02 · proprietary **score 60.7** ±1.3 · comparison only: no current run option verified · from 4 benchmark results across 3 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 Pro Experimental (02-05) among every model on that task or test, worst to best. 
task    vs the others          rank  counts  tests
coding  ▁▁▁▃▄▆█●▅▄▃▁   #209 of 539*     44%      1
math    ▁▁▃▆██●█▃▁▁▁   #205 of 530*     25%      1
coding · #209 of 539 · 44% of its score Beats [Qwen3.5 9B](qwen3-5-9b.md), [Gemini 2.5 Flash](gemini-2-5-flash.md), [Qwen3-VL 32B Thinking](qwen3-vl-32b-thinking.md) here, though they rank higher overall. 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…   35.6%  ▂·▂▃▅▂●█▆▄▂▂ beats 18/49  very hard · avg 7.6%     44%  sharp · at its level
math · #205 of 530 · 25% of its score Beats [MiniMax-M2.1](minimax-m2-1.md), [GPT-4.1](gpt-4-1.md) here, though they rank higher overall. Trails [Phi-4-mini-reasoning 3.8B](phi-4-mini-reasoning.md), [OpenThinker3 7B](openthinker3-7b.md), [Olmo 3 7B Think](olmo-3-7b-think.md) here, though they rank lower overall. 
test          result  vs the others in its run  difficulty      counts  why
MATH level 5   83.5%  ▂▂▅▆▄█▆▃●▂▃▄ beats 70/92  hard · avg 28%     25%  sharp
other tests (2) 
test                                result  vs the others in its run    difficulty           counts  why
GPQA Diamond                         65.7%  ▁▁▁▁▂▄▆▄●▇█▅ beats 96/211   hard · avg 39%          29%  sharp · at its level
Vectara hallucination leaderboard…   99.2%  ▁▁▂▃▄▄█▆▃▂▂● beats 139/140  very easy · avg 94%    0.7%  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
Epoch AI                                 2   55% ▇▇▇▇▇▇▇
Aider polyglot benchmark runs            1   44% ▇▇▇▇▇
Vectara hallucination leaderboard        1    1% ▇
prior: pull toward the middle                 1% ▇
weighted average                            = 60.7
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Aider polyglot benchmark runs ([Apache-2.0](../../licenses/aider-polyglot-runs-Apache-2.0.txt)) · 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-pro-exp-02-05) · [JSON](https://whatmodel.sh/api?format=json&all=1)