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Grok 4

SpaceXAIGrokProprietary

描述

Grok 4, announced by xAI in summer 2025, represents a major leap in AI capabilities, described as 'the smartest AI in the world.' Built on version 6 of xAI's foundation model, it uses 100x more training compute than Grok 2 and 10x more reinforcement learning compute than Grok 3. The model achieves PhD-level performance across all academic disciplines simultaneously, scoring perfect on standardized tests like the SAT and near-perfect on graduate exams like the GRE. Unlike Grok 3, tool usage is built into the training process rather than relying on generalization. Trained using 200,000 GPUs, Grok 4 excels at complex reasoning, mathematical problem-solving, and coding tasks, though it has acknowledged weaknesses in multimodal capabilities that are being addressed in the next version.

發布日期
2025-07-10
參數規模
上下文長度
支援模態
image, text

能力雷達圖

49
general
74
coding
94
reasoning
61
science
88
agents
80
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜81
75.0
AA
通用能力榜122
67.0
AA
科學能力87
72.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)87.5%自報

Code

LiveCodeBench79.0%自報

Math

AIME 202591.7%自報
HMMT2590.0%自報
Humanity's Last Exam40.0%自報
USAMO2537.5%自報

Reasoning

ARC-AGI v215.9%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
92.7
Intelligence Index(Artificial Analysis)
34.1
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
1.0
Aime(MAA (Mathematical Association of America))
0.9
Aime 25(MAA (Mathematical Association of America))
0.9
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.9
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.8
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.7
Lcr(Artificial Analysis)
0.7
Ifbench(Google Research (2023))
0.5
Scicode(UIUC + Argonne National Lab (2024))
0.5
Terminalbench Hard(Stanford × Laude Institute (2026))
0.4
Hle(Center for AI Safety + Scale AI (2025))
0.3

LLM Stats 分類評分

(LLM Stats (zeroeval))
Physics
90
Biology
90
Chemistry
90
Code
80
Math
60
Reasoning
60
General
60
Vision
30
Spatial Reasoning
20

定價

輸入價格$3 / 1M tokens
輸出價格$15 / 1M tokens
混合價格(3:1)$6 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

3 個供應商

最便宜: SpaceXAI最貴: LLM Gateway
供應商輸入輸出
1SpaceXAI主要
$3
$15
2Helicone
$3
$15
3LLM Gateway
$3
$15

比較該模型在不同 API 供應商之間的定價。

外部連結