[whatmodel.sh](../../README.md) / Grok 4.5
# Grok 4.5
SpaceXAI (xAI) · released 2026-07 · closed weights
**score 73.6** ±0.6 · #43 of 732 · from 21 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 4.5 among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅▄●▂▁ #34 of 313 18% 4
coding ▁▁▁▃▅▇█▇▅●▃▁ #41 of 469* 10% 2
chat & writing ▁▁▁▃▆▄▆█▆▇●▃ #39 of 402* 4.0% 1
math ▁▁▃▅█▆▄█●▂▁▁ #40 of 431 46% 5
vision & documents ▁▁▂▂▁▃▄▂▆▇●▄ #26 of 153* 4.1% 2
web search ▁▁▁▅▄●▃▄·▁·▁ #30 of 84* 1.5% 1
agent tasks · #34 of 313 · 18% of its score
Beats [GPT-5.6 Terra](gpt-5-6-terra.md), [GPT-5.6 Luna](gpt-5-6-luna.md), [Grok 4.6](grok-4-6.md) here, though they rank higher overall. Trails [Grok 4.7](grok-4-7.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena Agent (October 2026 aggrega… 0.0121 IPS ▁▁▁▃▃▂●▁▂▂▁▁ beats 30/59 avg -0.379 IPS 10% sharp
Terminal-Bench 4.0 12.4% ●▅▅▅▅·▅▃▃▅▅▅ beats 2/20 very hard · avg 0.5% 3.5% sharp
τ³-bench banking_knowledge (v1.0.… 47.9% ▃▃▂▃·▆▃▂█▅●▂ beats 23/25 very hard · avg 4.3% 2.7% at its level
EEGAgentBench overall (tool-based… 51.8% ▂·▁▁··▇▇●▂·▁ beats 22/25 hard · avg 28% 1.2% blunt · at its level
coding · #41 of 469 · 10% of its score
Beats [GPT-5.5](gpt-5-5.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [GPT-5.4](gpt-5-4.md) here, though they rank higher overall. Trails [Qwen3.8 27B](qwen3-8-27b.md), [GLM-5.2](glm-5-2.md), [GLM-5.3-Flash](glm-5-3-flash.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1553.0 ▁▁▃▂▅█▃●▅▅▁▂ beats 88/129 avg 981 7.2% sharp
Luau Leetcode fully solved (Torpe… 78.4% ▁▁▁▁·▁▂▃▅▃●▇ beats 30/49 hard · avg 17% 2.9% sharp · at its level
chat & writing · #39 of 402 · 4.0% of its score
Beats [GPT-6 Sol](gpt-6-sol.md), [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md), [Claude Haiku 5.5](claude-haiku-5-5.md) here, though they rank higher overall. Trails [MiMo-V2.5-Pro (1T-A42B)](mimo-v2-5-pro.md), [Grok 4.20 (0309 reasoning)](grok-4-20.md), [Claude Opus 4.5](claude-opus-4-5.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1465.4 ▁▁▁▂▃▃▃▆▆▇●▃ beats 341/385 avg 1260 4.0% blunt
math · #40 of 431 · 46% of its score
Beats [Claude Opus 4.7](claude-opus-4-7.md) here, though they rank higher overall. Trails [GPT-5.2](gpt-5-2.md), [Qwen3.7 Max](qwen3-7-max.md), [Muse Spark 1.1](muse-spark-1-1.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tiers 1–3 v2 57.2% ▂··▁▁▃▄▄●▆▄▃ beats 43/86 very hard · avg 1.2% 18% sharp · at its level
FrontierMath tier 4 v2 24.4% ▁▂▁▂●▅▂▃▂▁▁▁ beats 25/67 very hard · avg 0.1% 16% sharp · at its level
MathArena ArXivMath June 2026 (48… 66.7% ▂···▄·█●▆▆▄▂ beats 8/19 very hard · avg 5.1% 8.9% sharp · at its level
MathArena BrokenArXiv June 2026 (… 29.3% ▄··█▂●▂▆▄··▂ beats 7/14 very hard · avg 1.3% 2.0% sharp · at its level · noisy
OTIS mock AIME 2024–2025 97.8% ▃▃▄▃▃▃▇▇█▃●▅ beats 171/197 very hard · avg 7.2% 0.6% sharp · maxed out · noisy
vision & documents · #26 of 153 · 4.1% of its score
Beats [Claude Sonnet 5.5](claude-sonnet-5-5.md), [GPT-6 Sol](gpt-6-sol.md), [MiMo-V2.6-Pro](mimo-v2-6-pro.md) here, though they rank higher overall. Trails [Gemini 3.6 Flash](gemini-3-6-flash.md), [Gemini 3.5 Flash](gemini-3-5-flash.md), [Muse Spark 1.2](muse-spark-1-2.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1279.0 ▁▁▂▂▂▂▃▄▅▅█● beats 129/152 avg 1061 2.7% blunt
Arena document (style controlled) 1464.3 ▁▁▃▃▄▃▇●▅▇▄▅ beats 20/37 avg 1331 1.4% blunt
web search · #30 of 84 · 1.5% of its score
Beats [Claude Haiku 5.5](claude-haiku-5-5.md), [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md), [Claude Opus 4.7](claude-opus-4-7.md) here, though they rank higher overall. Trails [GPT-4o mini (2024-07-18)](gpt-4o-mini-2024-07-18.md), [Mistral Small 3.1 24B (2503)](mistral-small-3-1.md), [GPT-4o (2024-08-06)](gpt-4o-2024-08-06.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena search systems (style contr… 1206.2 ▁·▁▁▂▂▂█●▃▂▂ beats 23/36 avg 1069 1.5% blunt
other tests (6)
test result vs the others in its run difficulty counts why
Furniture Assembly (Epoch) 22.5% ●▆▆▆▆▂▆▂▂▂▂▅ beats 3/32 very hard · avg 1.2% 6.5% sharp · at its level
Chess Puzzles (Epoch) 36.0% █▁▁▁▁▂▃▃●▂▁▁ beats 113/137 very hard · avg 5.8% 3.6% sharp · at its level · noisy
GPQA Diamond 93.4% ▁▁▁▁▂▄▆▄▅▇█● beats 199/211 hard · avg 39% 2.9% sharp
SimpleQA Verified 48.3% ▁▁▃▂▃▃▆▆●▄▂▅ beats 51/81 very hard · avg 8.0% 1.6% at its level
MirrorCode (Epoch) 32.2% ▄·█▄▄▄●█·▄▄█ beats 7/13 very hard · avg 1.6% 1.0% sharp · at its level · noisy
RobloxQA v2.0 multiple choice (To… 96.2% ▁▁▃▁█▄▃▃●▂▂▂ beats 33/49 easy · avg 77% 1.0% maxed out
source results share of the score
Epoch AI 8 50% ▇▇▇▇▇▇
LMArena leaderboard dataset 6 27% ▇▇▇
MathArena ArXivMath / BrokenArXiv / ArX… 2 11% ▇
Roblox LLM Leaderboard 2 4% ▇
Terminal-Bench 4.0 official leaderboard… 1 4% ▇
τ²/τ³-bench leaderboard: Sierra's own e… 1 3% ▇
EEGAgentBench: Benchmarking LLM Agents … 1 1% ▇
prior: pull toward the middle 0% ▇
weighted average = 73.6
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/)) · MathArena ArXivMath / BrokenArXiv / ArXivLean model-output datasets ([CC BY-SA 4.0](../../licenses/matharena-sharealike-NOTICE.txt)) · Roblox LLM Leaderboard ([MIT](../../licenses/roblox-llm-leaderboard-MIT.txt)) · Terminal-Bench 4.0 official leaderboard submissions ([Apache-2.0](../../licenses/terminal-bench-leaderboard-submissions-Apache-2.0.txt)) · τ²/τ³-bench leaderboard: Sierra's own evaluation runs ([MIT](https://opensource.org/license/mit)) · EEGAgentBench: Benchmarking LLM Agents on Short- and Long-Horizon EEG Analysis ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))
## How to run it
### Through an API
api (xAI) · $3.00/M blended · $2 in / $6 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-4.5.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-4.5.toml)
[interactive version](https://whatmodel.sh/model/grok-4-5) · [JSON](https://whatmodel.sh/api?format=json&all=1)