Grok 4.7

Made by xAI, released 21 Sep 2026. Epoch AI lists its access as “API access”. Appears solid at knowledge among the models listed here.

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In short

What it does well

  • Knowledge: Strong (17th of 43 listed models)

Where it falls short

  • Coding: Behind the leaders (75th of 77 listed models)
  • Maths: Behind the leaders (35th of 43 listed models)
  • Writing: Behind the leaders (69th of 77 listed models)

What we don't know yet

  • Fixing real software bugs: Not enough data

The four ratings

  • Top tier
  • Strong
  • Middle
  • Behind the leaders
  • Not enough data

Ratings compare only the 77 models listed here, in quarters, best first. “Not enough data” means no result yet. It is never a low score.

Writing
Behind the leadersHow often people preferred its answers to writing prompts. 1,381 on Arena's scale · Source for Grok 4.7 writing score (lmarena)
Coding
Behind the leadersHow often people preferred its answers to coding questions. 1,428 on Arena's scale · Source for Grok 4.7 coding score (lmarena)
Maths
Behind the leadersHow many very hard maths problems it solved. 53.0% · Source for Grok 4.7 maths score (epoch)
Knowledge
StrongHow many short factual questions it answered correctly. 56.0% · Source for Grok 4.7 knowledge score (epoch)

Evidence completeness: Broad evidence, 12 of 13 tests have a result.

Where it is relatively stronger or weaker

This compares each kind of request with the model's own overall position among the 77 listed models, using Arena's votes. It is about performance on different languages, kinds of request and topics, not about political or social bias.

Relatively stronger

No category stands out as clearly stronger than its overall position.

Relatively weaker

No category stands out as clearly weaker than its overall position.

Show every category we can see
Position in each Arena category
CategoryPositionArena scoreVotesSource
Expert-level prompts
Kind of request
70th of 771,435
95% range 1,420 to 1,450
1,606Source for Expert-level prompts
Hard prompts
Kind of request
74th of 771,414
95% range 1,407 to 1,420
10,012Source for Hard prompts
Long prompts
Kind of request
72nd of 771,415
95% range 1,407 to 1,423
6,802Source for Long prompts
Longer conversations
Kind of request
75th of 771,394
95% range 1,382 to 1,407
2,465Source for Longer conversations
Chinese
Language
71st of 761,447
95% range 1,430 to 1,464
1,311Source for Chinese
English prompts
Language
72nd of 771,412
95% range 1,404 to 1,420
6,417Source for English prompts
French
Language
68th of 721,426
95% range 1,401 to 1,451
605Source for French
Japanese
Language
53rd of 541,357
95% range 1,323 to 1,390
337Source for Japanese
Non-English prompts
Language
76th of 771,384
95% range 1,377 to 1,391
9,983Source for Non-English prompts
Russian
Language
74th of 771,394
95% range 1,381 to 1,407
2,216Source for Russian
Spanish
Language
65th of 701,404
95% range 1,380 to 1,427
608Source for Spanish
Entertainment, sport and media
Topic
70th of 771,376
95% range 1,366 to 1,387
4,188Source for Entertainment, sport and media
Law and government
Topic
69th of 761,421
95% range 1,404 to 1,437
1,367Source for Law and government
Medicine and health
Topic
71st of 751,396
95% range 1,378 to 1,414
1,160Source for Medicine and health
Science
Topic
72nd of 771,416
95% range 1,404 to 1,428
2,770Source for Science
Software and IT
Topic
75th of 771,420
95% range 1,411 to 1,429
5,721Source for Software and IT

Bias: what we can and can't see

Our sources do not measure political lean, stereotyping, flattery (agreeing with you too readily) or safety behaviour, so we cannot say how any model does on those. What we can show is above: where a model is relatively stronger or weaker across languages, kinds of request and topics. Also, people voting in Arena can favour answer style, such as length and formatting, and our numbers do not adjust for that. See what AI bias means and what these tests can tell you.

Best-supported use cases

This model is not among the options we recommend for any of the five tasks. That reflects the rules and the models listed, not a verdict on the model.

Where an alternative might be more suitable

What it is

Maker
xAI
Release date (Epoch AI)
21 Sep 2026
Access, as listed by Epoch AI
API access
Licence, as listed by Arena
Proprietary
Maker's country (Epoch AI)
United States of America
Last observation in our data
28 Oct 2026
Data last changed
29 Oct 2026, 14:36 UTC

We have not verified an official product page for this model, so we do not link to one.

How you can use it

Proprietary. The model's files are not published, so it is generally available only through its maker or partners the maker chooses.

How you can reach it (an app, a website, a developer API or a third-party tool) and what that costs are not covered by our benchmark data. Where we could verify prices from the maker's own pages, they are shown under Price. Epoch AI lists access as “API access”. See models, apps and harnesses and how AI pricing works.

Price

Price not independently verified

See Grok (checked 29 Oct 2026). Page opened and read. It says Grok is 'free to try on the web and in the apps' and that SuperGrok adds higher limits. It states no prices or model names. The separate plans page opens as a sign-up pop-up showing introductory offers and no model names, so we record nothing else.

We never infer subscription prices from API prices. New to “tokens” and “per million”? See how AI pricing works.

Good to remember

  • Benchmarks are samples of tasks. None proves performance in every situation.
  • Arena scores come from people choosing between answers. That measures preference, not correctness.
  • Ratings are relative to the 77 models listed here. A different set would change them.
  • Sources test models at different settings. Each result shows the setting used, and we do not adjust it.

The evidence, for the curious

Show all 13 tests with settings and sources
All published results for Grok 4.7. Ratings compare only the 77 models on this site.
TestResultRatingSetting usedSource identifierObservedLinks
Arena text: overall preference
Arena 'text' leaderboard (Bradley-Terry rating, no style control)
1,398
Arena score
95% range 1,392 to 1,404, 16,442 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,381
Arena score
95% range 1,370 to 1,392, 3,673 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,428
Arena score
95% range 1,417 to 1,438, 3,617 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,413
Arena score
95% range 1,393 to 1,433, 862 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,406
Arena score
95% range 1,398 to 1,415, 5,493 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,390
Arena score
95% range 1,378 to 1,402, 2,800 votes
Behind the leaders effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · text/latest
28 Oct 2026 Source for Grok 4.7 Arena text: business and management score (lmarena)
Arena WebDev: building web apps
Arena 'webdev' leaderboard (Code Arena), category overall
1,637
Arena score
95% range 1,629 to 1,646, 6,572 votes
Top tier effort: xHigh, bradley-terry rating Grok 4.7 (xHigh)
lmarena · webdev/latest
28 Oct 2026 Source for Grok 4.7 Arena WebDev: building web apps score (lmarena)
FrontierMath Tiers 1-3 (v2)
FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12
53.0%
share of problems solved
standard error ±3.0 points
Behind the leaders effort: xhigh, best score across scorers grok-4.7_xhigh
epoch · frontiermath_tiers_1_3_v2.csv
22 Sep 2026 Source for Grok 4.7 FrontierMath Tiers 1-3 (v2) score (epoch)
No public run log in the data file.
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025, benchmark released 2024-12-19
98.1%
share of problems solved
standard error ±1.4 points
Strong effort: xhigh, best score across scorers grok-4.7_xhigh
epoch · otis_mock_aime_2024_2025.csv
22 Sep 2026 Source for Grok 4.7 OTIS Mock AIME 2024-2025 score (epoch)
No public run log in the data file.
GPQA Diamond
GPQA Diamond, benchmark released 2023-11-20
92.7%
share of questions correct
standard error ±1.6 points
Strong effort: xhigh, best score across scorers grok-4.7_xhigh
epoch · gpqa_diamond.csv
22 Sep 2026 Source for Grok 4.7 GPQA Diamond score (epoch)
No public run log in the data file.
SimpleQA Verified
SimpleQA Verified, benchmark released 2025-09-09
56.0%
share of questions correct
standard error ±1.6 points
Strong effort: xhigh, best score across scorers grok-4.7_xhigh
epoch · simpleqa_verified.csv
22 Sep 2026 Source for Grok 4.7 SimpleQA Verified score (epoch)
No public run log in the data file.
SWE-bench Verified (Epoch runs)Not enough data
FrontierCode (reported by Cognition)
FrontierCode, benchmark released 2026-06-08, aggregation Mean@5
47.6%
mean score over 5 attempts
no uncertainty figure published
Not rated (results use different tools) effort: high, tool: grok-build, mean@5 grok-4.7_unknown
epoch · frontiercode_external.csv
not provided Source for Grok 4.7 FrontierCode (reported by Cognition) score (epoch) · Run details for FrontierCode (reported by Cognition)

Missing evidence

Not enough data for these tests:

  • SWE-bench Verified (Epoch runs)

Missing results are not low scores and do not count against the model.

Where a source gives no public run log, we cannot show the run behind the score. See data sources.

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