Claude Opus 4.6

Made by Anthropic, released 5 Feb 2026. Epoch AI lists its access as “API access”. Appears strongest at coding and writing among the models listed here.

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In short

What it does well

  • Coding: Top tier (5th of 77 listed models)
  • Writing: Top tier (4th of 77 listed models)

Where it falls short

  • Knowledge: Middle (25th of 43 listed models)
  • Maths: Middle (24th 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
Top tierHow often people preferred its answers to writing prompts. 1,504 on Arena's scale · Source for Claude Opus 4.6 writing score (lmarena)
Coding
Top tierHow often people preferred its answers to coding questions. 1,531 on Arena's scale · Source for Claude Opus 4.6 coding score (lmarena)
Maths
MiddleHow many very hard maths problems it solved. 66.0% · Source for Claude Opus 4.6 maths score (epoch)
Knowledge
MiddleHow many short factual questions it answered correctly. 47.0% · Source for Claude Opus 4.6 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
6th of 771,543
95% range 1,535 to 1,550
7,698Source for Expert-level prompts
Hard prompts
Kind of request
5th of 771,525
95% range 1,521 to 1,529
53,763Source for Hard prompts
Long prompts
Kind of request
4th of 771,518
95% range 1,513 to 1,522
35,795Source for Long prompts
Longer conversations
Kind of request
2nd of 771,512
95% range 1,506 to 1,518
14,319Source for Longer conversations
Chinese
Language
6th of 761,551
95% range 1,542 to 1,559
5,913Source for Chinese
English prompts
Language
3rd of 771,512
95% range 1,507 to 1,516
37,010Source for English prompts
French
Language
3rd of 721,512
95% range 1,499 to 1,525
2,770Source for French
German
Language
6th of 551,502
95% range 1,485 to 1,519
1,336Source for German
Japanese
Language
12th of 541,487
95% range 1,467 to 1,508
986Source for Japanese
Korean
Language
13th of 541,450
95% range 1,433 to 1,467
1,417Source for Korean
Non-English prompts
Language
7th of 771,488
95% range 1,484 to 1,492
47,491Source for Non-English prompts
Russian
Language
11th of 771,495
95% range 1,488 to 1,501
9,833Source for Russian
Spanish
Language
3rd of 701,505
95% range 1,493 to 1,518
2,864Source for Spanish
Entertainment, sport and media
Topic
4th of 771,492
95% range 1,487 to 1,498
19,162Source for Entertainment, sport and media
Law and government
Topic
5th of 761,511
95% range 1,503 to 1,519
6,874Source for Law and government
Medicine and health
Topic
8th of 751,504
95% range 1,496 to 1,512
6,343Source for Medicine and health
Science
Topic
6th of 771,518
95% range 1,512 to 1,524
14,037Source for Science
Software and IT
Topic
6th of 771,525
95% range 1,521 to 1,530
31,981Source 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
Anthropic
Release date (Epoch AI)
5 Feb 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

Epoch lists more than one row for 'claude-opus-4-6' in swe_bench_verified.csv, so that result is not used.

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

What Anthropic's own page says about the Opus family (USD ($ as shown; the page does not state a currency code); checked 28 Oct 2026)

  • Free ($0): Opus not available
  • Pro ($20 per month billed monthly, or $17 per month billed annually ($200 up front)): Opus available
  • Max (From $100 per month): Opus available

The page marks plans against model families, not versions, so it does not say which version of a family a plan includes. Check that before relying on it.

See Claude plans and pricing (checked 28 Oct 2026). Page opened and read.

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 Claude Opus 4.6. 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)
1,502
Arena score
95% range 1,498 to 1,505, 84,512 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,504
Arena score
95% range 1,498 to 1,511, 15,580 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,531
Arena score
95% range 1,526 to 1,537, 21,789 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,518
Arena score
95% range 1,508 to 1,527, 4,364 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,521
Arena score
95% range 1,516 to 1,526, 27,276 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,497
Arena score
95% range 1,491 to 1,503, 16,500 votes
Top tier effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · text/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena text: business and management score (lmarena)
Arena WebDev: building web apps
Arena 'webdev' leaderboard (Code Arena), category overall
1,546
Arena score
95% range 1,541 to 1,552, 19,316 votes
Strong effort: High, bradley-terry rating Claude Opus 4.6 (High)
lmarena · webdev/latest
28 Oct 2026 Source for Claude Opus 4.6 Arena WebDev: building web apps score (lmarena)
FrontierMath Tiers 1-3 (v2)
FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12
66.0%
share of problems solved
standard error ±2.8 points
Middle effort: max, best score across scorers claude-opus-4-6_max
epoch · frontiermath_tiers_1_3_v2.csv
11 Jun 2026 Source for Claude Opus 4.6 FrontierMath Tiers 1-3 (v2) score (epoch) · Run details for FrontierMath Tiers 1-3 (v2)
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025, benchmark released 2024-12-19
91.1%
share of problems solved
standard error ±4.3 points
Middle effort: max, best score across scorers claude-opus-4-6_max
epoch · otis_mock_aime_2024_2025.csv
6 Aug 2026 Source for Claude Opus 4.6 OTIS Mock AIME 2024-2025 score (epoch) · Run details for OTIS Mock AIME 2024-2025
GPQA Diamond
GPQA Diamond, benchmark released 2023-11-20
88.4%
share of questions correct
standard error ±2.3 points
Middle effort: max, best score across scorers claude-opus-4-6_max
epoch · gpqa_diamond.csv
6 Aug 2026 Source for Claude Opus 4.6 GPQA Diamond score (epoch) · Run details for GPQA Diamond
SimpleQA Verified
SimpleQA Verified, benchmark released 2025-09-09
47.0%
share of questions correct
standard error ±1.6 points
Middle effort: max, best score across scorers claude-opus-4-6_max
epoch · simpleqa_verified.csv
27 Aug 2026 Source for Claude Opus 4.6 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
26.6%
mean score over 5 attempts
no uncertainty figure published
Not rated (results use different tools) effort: high, tool: claude-code, mean@5 claude-opus-4-6_unknown
epoch · frontiercode_external.csv
not provided Source for Claude Opus 4.6 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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