[whatmodel.sh](../../README.md) / ChatGPT-4o (2025-03-26) # ChatGPT-4o (2025-03-26) OpenAI · released 2025-03 · closed weights **score 64.6** ±1.5 · 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 ChatGPT-4o (2025-03-26) among every model on that task or test, worst to best. 
task                vs the others          rank  counts  tests
coding              ▁▁▁▃▄▆█●▅▄▃▁   #186 of 539*     60%      1
chat & writing      ▁▁▁▃▅▄▇█▇▇●▃    #69 of 474*     24%      1
vision & documents  ▁▁▂▃▂▃▅▄▆●█▄    #69 of 189*     16%      1
coding · #186 of 539 · 60% of its score Beats [Qwen3-Coder-Next (80B-A3B)](qwen3-coder-next.md), [Gemini 2.5 Pro](gemini-2-5-pro.md), [Gemini 3.1 Flash-Lite](gemini-3-1-flash-lite.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…   45.3%  ▂·▂▃▅▂▃●▆▄▂▂ beats 23/49  very hard · avg 7.6%     60%  sharp · at its level
chat & writing · #69 of 474 · 24% of its score Beats [Claude Haiku 5.5](claude-haiku-5-5.md), [GPT-6 Luna](gpt-6-luna.md), [Grok 4.7](grok-4-7.md) here, though they rank higher overall. 
test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1442.7  ▁▁▁▂▃▃▃▆▆▇●▃ beats 309/385  avg 1260       24%  blunt
vision & documents · #69 of 189 · 16% of its score Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5](gpt-5.md), [MiniMax-M3](minimax-m3.md) here, though they rank higher overall. Trails [Gemma 4 26B-A4B](gemma-4-26b-a4b.md) here, though they rank lower overall. 
test                             result  vs the others in its run   difficulty  counts  why
Arena vision (style controlled)  1238.6  ▁▁▂▂▂▂▃▄▅▅●▇ beats 94/152  avg 1061       16%  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
Aider polyglot benchmark runs        1   60% ▇▇▇▇▇▇▇
LMArena leaderboard dataset          2   39% ▇▇▇▇▇
prior: pull toward the middle             1% ▇
weighted average                        = 64.6
Licences: Aider polyglot benchmark runs ([Apache-2.0](../../licenses/aider-polyglot-runs-Apache-2.0.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/chatgpt-4o-latest-20250326) · [JSON](https://whatmodel.sh/api?format=json&all=1)