[whatmodel.sh](../../README.md) / Dola Seed 2.0 Pro # Dola Seed 2.0 Pro ByteDance · proprietary **score 72.2** ±2.0 · 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 Dola Seed 2.0 Pro among every model on that task or test, worst to best.}

task                vs the others         rank  counts  tests
agent tasks         ······●·····      #1 of 1*     31%      1
chat & writing      ▁▁▁▃▅▄▇█▇▇●▃   #53 of 474*     40%      1
vision & documents  ▁▁▂▃▂▃▅▄▆█●▄   #47 of 189*     27%      1

agent tasks · #1 of 1 · 31% of its score

test                      result  vs the others in its run  difficulty      counts  why
τ²-bench Telecom (maker)   94.2%  ▁·▅█▆▅▂▃●▂▃▁ beats 73/89  hard · avg 28%     31%  sharp · small run

chat & writing · #53 of 474 · 40% of its score

Beats [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md), [Claude Haiku 5.5](claude-haiku-5-5.md), [GPT-6 Luna](gpt-6-luna.md) here, though they rank higher overall. Trails [Gemini 3.5 Flash-Lite](gemini-3-5-flash-lite.md), [MiMo-V2.5-Pro (1T-A42B)](mimo-v2-5-pro.md), [GLM-5](glm-5.md) here, though they rank lower overall.

test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1456.1  ▁▁▁▂▃▃▃▆▆▇●▃ beats 331/385  avg 1260       40%  blunt

vision & documents · #47 of 189 · 27% of its score

Beats [MiMo-V2.6-Pro](mimo-v2-6-pro.md), [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md), [GPT-6 Luna](gpt-6-luna.md) here, though they rank higher overall. Trails [Qwen3.6 Flash](qwen3-6-flash.md), [Gemini 3.5 Flash-Lite](gemini-3-5-flash-lite.md), [Qwen3.6 Plus](qwen3-6-plus.md) here, though they rank lower overall.

test                             result  vs the others in its run    difficulty  counts  why
Arena vision (style controlled)  1256.5  ▁▁▂▂▂▂▃▄▅▅●▇ beats 112/152  avg 1061       27%  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   67% ▇▇▇▇▇▇▇▇
ByteDance Seed - Seed2.0 Model Card (su…        1   31% ▇▇▇▇
prior: pull toward the middle                        2% ▇
weighted average                                   = 72.2

_{Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · ByteDance Seed - Seed2.0 Model Card ([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/dola-seed-2-0-pro) · [JSON](https://whatmodel.sh/api?format=json&all=1)