[whatmodel.sh](../../README.md) / Grok 4 (0709)
# Grok 4 (0709)
SpaceXAI (xAI) · released 2025-07 · proprietary
**score 67.3** ±1.1 · comparison only: no current run option verified · from 11 benchmark results across 7 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Grok 4 (0709) among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▂▆█▄●▄▄▃▁▁ #151 of 354* 8.7% 2
coding ▁▁▁▃▄▆█▇●▄▃▁ #96 of 539* 27% 1
chat & writing ▁▁▁▃▅▄▇█▇●▇▃ #118 of 474* 13% 1
math ▁▁▃▆██▅●▃▁▁▁ #103 of 530* 6.4% 1
vision & documents ▁▁▂▃▂▃▅●▆██▄ #106 of 189* 8.5% 1
web search ▂▁●▆▅█▅▄▁▂▁▁ #85 of 96* 4.6% 1
agent tasks · #151 of 354 · 8.7% of its score
Beats [o3](o3.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Large](jamba-1-5-large.md), [GPT-4o (2024-05-13)](gpt-4o-2024-05-13.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
BFCL V4 (December 2025 archive) 61.4% ▁▁▁▂██▅▅▆●▂▂ beats 71/77 hard · avg 31% 6.0% at its level
Galileo Agent Leaderboard v2 (act… 42.0% ▅▃·▃▃▅▅●▃█▅▅ beats 9/19 hard · avg 26% 2.7% at its level
coding · #96 of 539 · 27% of its score
Beats [Grok 4.20 (0309 reasoning)](grok-4-20.md), [GPT-5.4 mini](gpt-5-4-mini.md), [GPT-5.1](gpt-5-1.md) here, though they rank higher overall. Trails [Llama 3.1 Nemotron Ultra 253B v1](llama-3-1-nemotron-ultra-253b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Aider polyglot (225 exercises, tw… 79.6% ▂·▂▃▅▂▃█▆▄●▂ beats 45/49 very hard · avg 7.6% 27% sharp · at its level
chat & writing · #118 of 474 · 13% of its score
Beats [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [Inkling Small (266B-A12B)](inkling-small.md), [GPT-5.4 nano](gpt-5-4-nano.md) here, though they rank higher overall. Trails [Mistral Large 3 (675B-A41B)](mistral-large-3.md), [Gemma 4 12B](gemma-4-12b.md), [Qwen3-VL 235B-A22B Instruct](qwen3-vl-235b-a22b-instruct.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1411.0 ▁▁▁▂▃▃▃▆▆●█▃ beats 257/385 avg 1260 13% blunt
math · #103 of 530 · 6.4% of its score
Beats [Claude Sonnet 4.6](claude-sonnet-4-6.md), [MiniMax-M3](minimax-m3.md), [Nemotron 3 Ultra 550B-A55B](nemotron-3-ultra-550b-a55b.md) here, though they rank higher overall. Trails [Gemini 2.5 Flash](gemini-2-5-flash.md), [Granite 4.2 30B](granite-4-2-30b.md), [Qwen3-Next 80B-A3B Instruct](qwen3-next-80b-a3b-instruct.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
OTIS mock AIME 2024–2025 84.0% ▃▃▄▃▃▃▇●█▃▂▅ beats 122/197 very hard · avg 7.2% 6.4% sharp · noisy
vision & documents · #106 of 189 · 8.5% of its score
Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md) here, though they rank higher overall. Trails [Qwen3.5 4B](qwen3-5-4b.md), [GPT-4.1 mini](gpt-4-1-mini.md), [Mistral Large 3 (675B-A41B)](mistral-large-3.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1184.2 ▁▁▂▂▂▂▃▄●▅█▇ beats 62/152 avg 1061 8.5% blunt
web search · #85 of 96 · 4.6% of its score
Beats [Nemotron 3 Ultra 550B-A55B](nemotron-3-ultra-550b-a55b.md) here, though they rank higher overall. Trails [GPT-4.1 nano](gpt-4-1-nano-2025-04-14.md), [GPT-4o mini (2024-07-18)](gpt-4o-mini-2024-07-18.md), [Mistral Small 3.1 24B (2503)](mistral-small-3-1.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena search systems (style contr… 1122.7 ▁·●▁▂▂▂█▆▃▂▂ beats 1/36 avg 1069 4.6% blunt
other tests (4)
test result vs the others in its run difficulty counts why
GPQA Diamond 87.0% ▁▁▁▁▂▄▆▄▅▇●▅ beats 155/211 hard · avg 39% 17% sharp · at its level
EQ-Bench 3 (emotional intelligenc… 1190.3 ▁·▂▁▄▅●▃█▄▁▁ beats 29/62 avg 1034 7.8% typical
Chess Puzzles (Epoch) 28.0% █▁▁▁▁▂▃●▃▂▁▁ beats 101/137 very hard · avg 5.8% 6.2% sharp · noisy
Vectara hallucination leaderboard… 95.2% ▁▁▂▃▄▄●▆▃▂▂▁ beats 63/140 very easy · avg 94% 0.4% blunt · maxed out · noisy
source results share of the score
Epoch AI 3 29% ▇▇▇▇
Aider polyglot benchmark runs 1 27% ▇▇▇
LMArena leaderboard dataset 3 26% ▇▇▇
EQ-Bench 3 canonical leaderboard results 1 8% ▇
Berkeley Function Calling Leaderboard r… 1 6% ▇
Galileo Agent Leaderboard 1 3% ▇
Vectara hallucination leaderboard 1 0% ▇
prior: pull toward the middle 1% ▇
weighted average = 67.3
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)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · EQ-Bench 3 canonical leaderboard results ([MIT](../../licenses/eqbench3-MIT.txt)) · Berkeley Function Calling Leaderboard result archive ([Apache-2.0](../../licenses/bfcl-result-archive-v4-Apache-2.0.txt)) · Galileo Agent Leaderboard ([Apache-2.0](../../licenses/galileo-agent-leaderboard-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/grok-4-0709) · [JSON](https://whatmodel.sh/api?format=json&all=1)