Grok 4.5

Made by xAI, released 8 Jul 2026. Epoch AI lists its access as “API access”. Appears solid at writing among the models listed here.

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In short

What it does well

  • Writing: Strong (33rd of 77 listed models)

Where it falls short

  • Coding: Middle (46th of 77 listed models)
  • Knowledge: Middle (24th of 43 listed models)
  • Maths: Middle (32nd of 43 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
StrongHow often people preferred its answers to writing prompts. 1,442 on Arena's scale · Source for Grok 4.5 writing score (lmarena)
Coding
MiddleHow often people preferred its answers to coding questions. 1,474 on Arena's scale · Source for Grok 4.5 coding score (lmarena)
Maths
MiddleHow many very hard maths problems it solved. 57.2% · Source for Grok 4.5 maths score (epoch)
Knowledge
MiddleHow many short factual questions it answered correctly. 48.3% · Source for Grok 4.5 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
52nd of 771,465
95% range 1,455 to 1,474
4,708Source for Expert-level prompts
Hard prompts
Kind of request
45th of 771,462
95% range 1,457 to 1,467
26,590Source for Hard prompts
Long prompts
Kind of request
38th of 771,462
95% range 1,456 to 1,468
19,221Source for Long prompts
Longer conversations
Kind of request
42nd of 771,456
95% range 1,448 to 1,464
6,634Source for Longer conversations
Chinese
Language
46th of 761,494
95% range 1,483 to 1,506
3,036Source for Chinese
English prompts
Language
53rd of 771,453
95% range 1,447 to 1,458
16,168Source for English prompts
French
Language
52nd of 721,457
95% range 1,439 to 1,475
1,283Source for French
German
Language
41st of 551,446
95% range 1,423 to 1,469
684Source for German
Japanese
Language
30th of 541,429
95% range 1,402 to 1,456
544Source for Japanese
Korean
Language
45th of 541,403
95% range 1,380 to 1,425
739Source for Korean
Non-English prompts
Language
45th of 771,440
95% range 1,435 to 1,445
23,631Source for Non-English prompts
Russian
Language
44th of 771,450
95% range 1,441 to 1,459
4,584Source for Russian
Spanish
Language
43rd of 701,451
95% range 1,432 to 1,469
1,077Source for Spanish
Entertainment, sport and media
Topic
39th of 771,433
95% range 1,426 to 1,440
10,323Source for Entertainment, sport and media
Law and government
Topic
40th of 761,463
95% range 1,452 to 1,474
3,322Source for Law and government
Medicine and health
Topic
59th of 751,440
95% range 1,428 to 1,452
2,923Source for Medicine and health
Science
Topic
41st of 771,465
95% range 1,457 to 1,472
6,520Source for Science
Software and IT
Topic
47th of 771,471
95% range 1,465 to 1,477
15,970Source 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)
8 Jul 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 4.5. 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)
1,448
Arena score
95% range 1,443 to 1,452, 39,801 votes
Middle effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,442
Arena score
95% range 1,434 to 1,450, 8,215 votes
Strong effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,474
Arena score
95% range 1,467 to 1,481, 11,123 votes
Middle effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,459
Arena score
95% range 1,445 to 1,473, 1,756 votes
Middle effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,445
Arena score
95% range 1,439 to 1,451, 14,483 votes
Middle effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,441
Arena score
95% range 1,434 to 1,449, 7,618 votes
Middle effort: not stated, bradley-terry rating Grok 4.5
lmarena · text/latest
28 Oct 2026 Source for Grok 4.5 Arena text: business and management score (lmarena)
Arena WebDev: building web apps
Arena 'webdev' leaderboard (Code Arena), category overall
1,553
Arena score
95% range 1,546 to 1,560, 11,018 votes
Strong effort: not stated, bradley-terry rating Grok 4.5
lmarena · webdev/latest
28 Oct 2026 Source for Grok 4.5 Arena WebDev: building web apps score (lmarena)
FrontierMath Tiers 1-3 (v2)
FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12
57.2%
share of problems solved
standard error ±2.9 points
Middle effort: high, best score across scorers grok-4.5_high
epoch · frontiermath_tiers_1_3_v2.csv
9 Jul 2026 Source for Grok 4.5 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
97.8%
share of problems solved
standard error ±1.3 points
Strong effort: high, best score across scorers grok-4.5_high
epoch · otis_mock_aime_2024_2025.csv
8 Jul 2026 Source for Grok 4.5 OTIS Mock AIME 2024-2025 score (epoch)
No public run log in the data file.
GPQA Diamond
GPQA Diamond, benchmark released 2023-11-20
93.4%
share of questions correct
standard error ±1.4 points
Top tier effort: high, best score across scorers grok-4.5_high
epoch · gpqa_diamond.csv
8 Jul 2026 Source for Grok 4.5 GPQA Diamond score (epoch)
No public run log in the data file.
SimpleQA Verified
SimpleQA Verified, benchmark released 2025-09-09
48.3%
share of questions correct
standard error ±1.6 points
Middle effort: high, best score across scorers grok-4.5_high
epoch · simpleqa_verified.csv
27 Aug 2026 Source for Grok 4.5 SimpleQA Verified score (epoch) · Run details for SimpleQA Verified
SWE-bench Verified (Epoch runs)Not enough data
FrontierCode (reported by Cognition)
FrontierCode, benchmark released 2026-06-08, aggregation Mean@5
42.4%
mean score over 5 attempts
no uncertainty figure published
Not rated (results use different tools) effort: high, tool: grok-build, mean@5 grok-4.5_unknown
epoch · frontiercode_external.csv
not provided Source for Grok 4.5 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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