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Grok 4.5

xAI

Released
July 16, 2026
Data date
August 11, 2026

Category view

Position within the category

This overview uses only published data from matching cohorts. Missing values never change a rank.

The index averages rank percentiles from 4 documented comparison cohorts. Only models with complete coverage receive a position.

Position
Rank 15 of 26
Index score
46.2 / 100
Coverage
4 / 4

Leaderboard

1Claude Opus 588.9 / 100
2Gemini 3.8 Flash88.5 / 100
3Claude Fable 583.2 / 100
14GLM-5.354.8 / 100
15Grok 4.5, Current model46.2 / 100
16Gemini 3.1 Pro Preview41.3 / 100
25MiMo-V2.5-Pro12.5 / 100

Measurements

Comparable benchmark results

Each chart contains exactly one source, one measurement series, and one stored comparison cohort. Bars show the position. The measured value appears on the right.

SimpleQA Verified v2

53.8% · Rank 5 of 5

Task: Kaggle score · Comparison cohort: simpleqa-verified-v2:official:overall · Data date: August 9, 2026

1.Gemini 3.1 Pro Preview77.5%
2.Gemini 3.5 Flash70.4%
3.GPT-5.6 Sol69.2%
4.Claude Opus 563.3%
5.Grok 4.5, Current model53.8%

5 of 5 model versions shown in this chart. A higher value ranks first.

1,000 verified prompts without tools. Kaggle independently reproduced the results.

Source: KaggleParticipants: 5

SWE-Marathon v1.0

29% · Rank 1 of 4

Task: Binary resolution, pass@1 · Comparison cohort: swe-marathon-v1-0:official:pass1 · Data date: August 9, 2026

1.Grok 4.5, Current model29%
2.Claude Fable 524%
3.GPT-5.512%
4.Gemini 3.5 Flash7%

4 of 4 model versions shown in this chart. A higher value ranks first.

20 multi-hour tasks. The named coding agent is part of every result row.

Source: SWE-MarathonParticipants: 4

Profile

Specifications and access

Published information about this model. Unknown values are not estimated.

Model type
ProprietarySource
Context window
500,000 tokensSource
Knowledge cutoff
February 1, 2026Source
Notes
Coding/agentic flagship (first release under SpaceXAI), 500K context, parameter count not disclosedSource

Pricing

Published prices

Prices remain tied to their documented unit and source.

API input
$2 per 1M tokensSource
API input
$4 per 1M tokens (above 200,000 context tokens)Source
API output
$6 per 1M tokensSource
API output
$12 per 1M tokens (above 200,000 context tokens)Source
Cache read
$0.3 per 1M tokensSource
Cache read
$0.6 per 1M tokens (above 200,000 context tokens)Source

Head-to-head comparisons

Compare this model

Each matchup compares this model with exactly one other model from the same category.

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Evidence

Primary sources and data date

Every statement links to its underlying documentation or leaderboard.

  • Model metadataSource
  • API pricingSource
  • Kaggle (retrieved August 9, 2026)Source
  • SWE-Marathon (retrieved August 9, 2026)Source