[whatmodel.sh](../../README.md) / Grok 4.3
# Grok 4.3
SpaceXAI (xAI) · released 2026-04 · closed weights
**score 69.1** ±0.8 · #87 of 732 · from 15 benchmark results across 6 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Grok 4.3 among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄●▅▄▄▂▁ #121 of 313 10% 4
coding ▁▁▁▃▅▇█▇●▄▃▁ #120 of 469* 12% 1
chat & writing ▁▁▁▃▆▄▆█▆▇●▃ #62 of 402* 6.8% 1
math ▁▁▃▅█▆▄█●▂▁▁ #61 of 431 47% 3
vision & documents ▁▁▂▂▁▃▄▂▆●█▄ #57 of 153* 4.6% 1
web search ▁▁▁●▄█▃▄·▁·▁ #67 of 84* 4.4% 2
agent tasks · #121 of 313 · 10% of its score
Beats [o3-pro](o3-pro.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Large](jamba-1-5-large.md), [Devstral 2 (2512)](devstral-2.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Agents' Last Exam overall full-pa… 4.3% ●···█▄▄▄█▄·█ beats 0/10 very hard · avg 1.9% 4.1% typical
Thinkingbox-bench pass@1 (507 sta… 14.4% ▅··●·▃·█▃▅██ beats 2/15 very hard · avg 5.1% 2.7% sharp · at its level
Legal Research Bench (agentic, al… 15.3% ▄●··▄▄▄██·▄█ beats 1/12 very hard · avg 6.3% 1.9% typical
KlinikeBench strict pass@1 (333 i… 21.3% ▁▁·▁▁▁▁▅▃█●█ beats 19/27 very hard · avg 2.4% 1.4% typical
coding · #120 of 469 · 12% of its score
Trails [Llama 3.1 Nemotron Ultra 253B v1](llama-3-1-nemotron-ultra-253b.md), [Solar Pro 4](solar-pro-4.md), [Laguna XS 2.1 (33B-A3B)](laguna-xs-2-1.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1357.6 ▁▁▃▂●█▃▆▅▅▁▂ beats 30/129 avg 981 12% sharp
chat & writing · #62 of 402 · 6.8% 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. Trails [Gemma 4 31B](gemma-4-31b.md), [Gemini 2.5 Pro](gemini-2-5-pro.md), [Claude Sonnet 4.5](claude-sonnet-4-5.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1441.6 ▁▁▁▂▃▃▃▆▆▇●▃ beats 307/385 avg 1260 6.8% blunt
math · #61 of 431 · 47% of its score
Beats [Qwen3.6 Max Preview](qwen3-6-max-preview.md), [Claude Sonnet 4.6](claude-sonnet-4-6.md), [DeepSeek V4 Pro (Preview, Apr 2026)](deepseek-v4-pro-preview.md) here, though they rank higher overall. Trails [INTELLECT-3](intellect-3.md), [A.X K2 (688B-A33B)](ax-k2.md), [Inkling Small (266B-A12B)](inkling-small.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tiers 1–3 v2 42.8% ▂··▁▁▃▄●█▆▄▃ beats 29/86 very hard · avg 1.2% 32% sharp · at its level
FrontierMath tier 4 v2 14.6% ▁▂▁▂●▅▂▃▂▁▁▁ beats 15/67 very hard · avg 0.1% 13% sharp
OTIS mock AIME 2024–2025 93.3% ▃▃▄▃▃▃▇▇●▃▂▅ beats 153/197 very hard · avg 7.2% 2.6% sharp · noisy
vision & documents · #57 of 153 · 4.6% of its score
Beats [GPT-6 Luna](gpt-6-luna.md), [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5](gpt-5.md) here, though they rank higher overall. Trails [Qwen3.6 Flash](qwen3-6-flash.md), [Qwen3.5 35B-A3B](qwen3-5-35b-a3b.md), [Gemma 4 31B](gemma-4-31b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1242.3 ▁▁▂▂▂▂▃▄▅▅●▇ beats 97/152 avg 1061 4.6% blunt
web search · #67 of 84 · 4.4% of its score
Beats [DeepSeek V4 Flash (Preview, Apr 2026)](deepseek-v4-flash-preview.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… 1192.8 ▁·▁▁▂▂▂●▆▃▂▂ beats 15/36 avg 1069 2.5% blunt
Legal Research Bench (agentic, al… 15.3% ▄●··▄▄▄██·▄█ beats 1/12 very hard · avg 6.3% 1.9% typical
other tests (4)
test result vs the others in its run difficulty counts why
GPQA Diamond 88.8% ▁▁▁▁▂▄▆▄▅▇●▅ beats 167/211 hard · avg 39% 7.8% sharp
Chess Puzzles (Epoch) 25.0% █▁▁▁▁▂▃●▃▂▁▁ beats 95/137 very hard · avg 5.8% 4.0% sharp · noisy
SimpleQA Verified 33.2% ▁▁▃▂▃▃●▆█▄▂▅ beats 24/81 very hard · avg 8.0% 2.5% at its level
Legal Research Bench (single-shot… 4.1% ▃▃█▃·●···█▃▃ beats 6/12 very hard · avg 0.8% 2.1% too hard for it
source results share of the score
Epoch AI 6 62% ▇▇▇▇▇▇▇
LMArena leaderboard dataset 4 26% ▇▇▇
Agents' Last Exam 1 4% ▇
Legal Research Bench 2 4% ▇
One Success Isn't Reliability: Thinking… 1 3% ▇
KlinikeBench: Evaluating Language Model… 1 1% ▇
prior: pull toward the middle 0% ▇
weighted average = 69.1
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Agents' Last Exam ([CC BY 4.0](../../licenses/paper-2606.05405v2-CC-BY-4.0.txt)) · Legal Research Bench ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · One Success Isn't Reliability: Thinkingbox ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))
## How to run it
### Through an API
api (xAI) · $1.56/M blended · $1.25 in / $2.5 out per 1M tokens · [docs.x.ai](https://docs.x.ai/docs/models)
[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/xai/models/grok-4.3.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/xai/grok-4.3.toml)
[interactive version](https://whatmodel.sh/model/grok-4-3) · [JSON](https://whatmodel.sh/api?format=json&all=1)