[whatmodel.sh](../../README.md) / Gemini 2.0 Flash Thinking Experimental (01-21) # Gemini 2.0 Flash Thinking Experimental (01-21) Google · released 2025-01 · proprietary **score 57.4** ±1.4 · 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 Flash Thinking Experimental (01-21) among every model on that task or test, worst to best.}

task         vs the others          rank  counts  tests
agent tasks  ▁▁▂▆●▄▅▄▄▃▁▁   #259 of 354*    4.6%      1
coding       ▁▁▁▃▄▆●▇▅▄▃▁   #275 of 539*     45%      1
math         ▁▁▃▆██●█▃▁▁▁   #181 of 530*     15%      1

agent tasks · #259 of 354 · 4.6% of its score

Beats [o1 (2024-12-17)](o1-2024-12-17.md), [o3-mini](o3-mini.md), [DeepSeek R1 (Jan '25)](deepseek-r1.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Mini](jamba-1-5-mini.md), [LFM2.5 1.2B Thinking](lfm2-5-1-2b-thinking.md) here, though they rank lower overall.

test     result  vs the others in its run   difficulty        counts  why
BFCL v3   58.7%  ▁▁▁▁▁▃▅█●▄▁▁ beats 79/114  medium · avg 51%    4.6%  blunt · at its level

coding · #275 of 539 · 45% of its score

Beats [Qwen3.5 4B](qwen3-5-4b.md), [Qwen3-VL 32B Instruct](qwen3-vl-32b-instruct.md), [Solar Open 100B (102B-A12B)](solar-open-100b.md) here, though they rank higher overall. Trails [QwQ-32B-Preview](qwq-32b-preview.md), [Ministral 3 3B Reasoning 2512](ministral-3-3b-reasoning.md), [GPT-4 (0613)](gpt-4-0613.md) here, though they rank lower overall.

test                                result  vs the others in its run  difficulty            counts  why
Aider polyglot (225 exercises, tw…   18.2%  ▂·▂▃●▂▃█▆▄▂▂ beats 9/49   very hard · avg 7.6%     45%  sharp · at its level

math · #181 of 530 · 15% of its score

Beats [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md), [MiniMax-M2.7](minimax-m2-7.md), [MiniMax-M2.1](minimax-m2-1.md) here, though they rank higher overall. Trails [Olmo 3 7B Think](olmo-3-7b-think.md), [Nemotron Nano 9B v2](nemotron-nano-9b-v2.md), [Qwen3-VL 4B Thinking](qwen3-vl-4b-thinking.md) here, though they rank lower overall.

test                      result  vs the others in its run   difficulty            counts  why
OTIS mock AIME 2024–2025   57.8%  ▃▃▄▃▃▃●▇█▃▂▅ beats 86/197  very hard · avg 7.2%     15%  sharp · at its level · noisy

other tests (1)

test          result  vs the others in its run   difficulty      counts  why
GPQA Diamond   57.1%  ▁▁▁▁▂▄▆●▅▇█▅ beats 85/211  hard · avg 39%     35%  sharp · at its level

## 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   50% ▇▇▇▇▇▇
Aider polyglot benchmark runs                   1   45% ▇▇▇▇▇
Berkeley Function Calling Leaderboard r…        1    5% ▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 57.4

_{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)) · 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-2-0-flash-thinking-exp-01-21) · [JSON](https://whatmodel.sh/api?format=json&all=1)