GPT-6.1 Sol

Made by OpenAI, released 29 Sep 2026. Epoch AI lists its access as “API access”. Appears strongest at knowledge and maths among the models listed here.

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In short

What it does well

  • Knowledge: Top tier (3rd of 43 listed models)
  • Maths: Top tier (1st of 43 listed models)
  • Coding: Strong (37th of 77 listed models)

Where it falls short

  • Writing: Middle (54th 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
MiddleHow often people preferred its answers to writing prompts. 1,425 on Arena's scale · Source for GPT-6.1 Sol writing score (lmarena)
Coding
StrongHow often people preferred its answers to coding questions. 1,486 on Arena's scale · Source for GPT-6.1 Sol coding score (lmarena)
Maths
Top tierHow many very hard maths problems it solved. 93.7% · Source for GPT-6.1 Sol maths score (epoch)
Knowledge
Top tierHow many short factual questions it answered correctly. 73.9% · Source for GPT-6.1 Sol 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

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
26th of 771,499
95% range 1,479 to 1,519
849Source for Expert-level prompts
Hard prompts
Kind of request
41st of 771,467
95% range 1,459 to 1,476
5,478Source for Hard prompts
Long prompts
Kind of request
37th of 771,463
95% range 1,452 to 1,474
3,739Source for Long prompts
Longer conversations
Kind of request
61st of 771,442
95% range 1,425 to 1,459
1,301Source for Longer conversations
Chinese
Language
52nd of 761,491
95% range 1,471 to 1,511
868Source for Chinese
English prompts
Language
51st of 771,453
95% range 1,442 to 1,464
3,551Source for English prompts
French
Language
49th of 721,464
95% range 1,433 to 1,494
381Source for French
Non-English prompts
Language
49th of 771,436
95% range 1,427 to 1,444
5,812Source for Non-English prompts
Russian
Language
39th of 771,457
95% range 1,441 to 1,474
1,352Source for Russian
Spanish
Language
53rd of 701,442
95% range 1,410 to 1,474
326Source for Spanish
Entertainment, sport and media
Topic
42nd of 771,428
95% range 1,414 to 1,441
2,338Source for Entertainment, sport and media
Law and government
Topic
32nd of 761,474
95% range 1,452 to 1,496
761Source for Law and government
Medicine and health
Topic
62nd of 751,431
95% range 1,408 to 1,454
668Source for Medicine and health
Science
Topic
64th of 771,448
95% range 1,433 to 1,464
1,586Source for Science
Software and IT
Topic
42nd of 771,481
95% range 1,469 to 1,492
3,156Source 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

Where an alternative might be more suitable

What it is

Maker
OpenAI
Release date (Epoch AI)
29 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

Verified consumer plans that include this model

  • ChatGPT Plus: GBP 20.00 per month. Maker's page, checked 29 Oct 2026. Comparison table cell for this model on this plan: "Yes". The page says limits apply.
  • ChatGPT Pro (from): GBP 89.00 per month. Maker's page, checked 29 Oct 2026. Comparison table cell for this model on this plan: "Expanded". Listed as 'From £89 / month' with a choice of 3 usage tiers.

Prices change and can differ by country. Check the maker's page before you pay.

See ChatGPT plans and pricing (checked 29 Oct 2026). Page opened and read in the browser. Which plan includes which model comes from its comparison table.

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 GPT-6.1 Sol. 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)
1,446
Arena score
95% range 1,439 to 1,453, 9,367 votes
Middle effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,425
Arena score
95% range 1,411 to 1,439, 2,069 votes
Middle effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,486
Arena score
95% range 1,472 to 1,500, 1,896 votes
Strong effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,486
Arena score
95% range 1,461 to 1,511, 519 votes
Strong effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,467
Arena score
95% range 1,456 to 1,479, 2,892 votes
Strong effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,449
Arena score
95% range 1,433 to 1,464, 1,509 votes
Strong effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · text/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena text: business and management score (lmarena)
Arena WebDev: building web apps
Arena 'webdev' leaderboard (Code Arena), category overall
1,751
Arena score
95% range 1,739 to 1,762, 4,092 votes
Top tier effort: Max, bradley-terry rating GPT-6.1 Sol (Max)
lmarena · webdev/latest
28 Oct 2026 Source for GPT-6.1 Sol Arena WebDev: building web apps score (lmarena)
FrontierMath Tiers 1-3 (v2)
FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12
93.7%
share of problems solved
standard error ±1.4 points
Top tier effort: max, best score across scorers gpt-6.1-sol_max
epoch · frontiermath_tiers_1_3_v2.csv
29 Sep 2026 Source for GPT-6.1 Sol 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
100.0%
share of problems solved
standard error ±0.0 points
Top tier effort: max, best score across scorers gpt-6.1-sol_max
epoch · otis_mock_aime_2024_2025.csv
29 Sep 2026 Source for GPT-6.1 Sol OTIS Mock AIME 2024-2025 score (epoch)
No public run log in the data file.
GPQA Diamond
GPQA Diamond, benchmark released 2023-11-20
95.4%
share of questions correct
standard error ±1.4 points
Top tier effort: max, best score across scorers gpt-6.1-sol_max
epoch · gpqa_diamond.csv
29 Sep 2026 Source for GPT-6.1 Sol GPQA Diamond score (epoch)
No public run log in the data file.
SimpleQA Verified
SimpleQA Verified, benchmark released 2025-09-09
73.9%
share of questions correct
standard error ±1.4 points
Top tier effort: max, best score across scorers gpt-6.1-sol_max
epoch · simpleqa_verified.csv
29 Sep 2026 Source for GPT-6.1 Sol 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
50.2%
mean score over 5 attempts
no uncertainty figure published
Not rated (results use different tools) effort: medium, tool: codex, mean@5 gpt-6.1-sol_medium
epoch · frontiercode_external.csv
not provided Source for GPT-6.1 Sol 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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