ERNIE 5.1

Made by Baidu. Epoch AI does not state how it can be accessed. Appears solid at coding and writing among the models listed here.

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In short

What it does well

  • Coding: Strong (34th of 77 listed models)
  • Writing: Strong (36th of 77 listed models)

Where it falls short

The four main ratings show no weakness. That is not evidence it has none.

What we don't know yet

  • Web-building votes: Not enough data
  • Hard maths problems: Not enough data
  • School-competition maths: Not enough data
  • Graduate-level science questions: Not enough data
  • Short factual questions: Not enough data
  • Fixing real software bugs: Not enough data
  • Difficult coding tasks: 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. 1,441 on Arena's scale · Source for ERNIE 5.1 writing score (lmarena)
Coding
StrongHow often people preferred its answers to coding questions. 1,488 on Arena's scale · Source for ERNIE 5.1 coding score (lmarena)
Maths
Not enough dataNo result yet for hard maths problems.
Knowledge
Not enough dataNo result yet for short factual questions.

Evidence completeness: Thin evidence, 6 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

  • Japanese: 35th of 54 on questions asked in Japanese, against 30th of 77 overall. Source for Japanese
Show every category we can see
Position in each Arena category
CategoryPositionArena scoreVotesSource
Expert-level prompts
Kind of request
31st of 771,491
95% range 1,481 to 1,501
3,728Source for Expert-level prompts
Hard prompts
Kind of request
32nd of 771,481
95% range 1,475 to 1,486
25,670Source for Hard prompts
Long prompts
Kind of request
39th of 771,462
95% range 1,456 to 1,468
16,715Source for Long prompts
Longer conversations
Kind of request
30th of 771,470
95% range 1,462 to 1,478
6,809Source for Longer conversations
Chinese
Language
38th of 761,507
95% range 1,493 to 1,520
2,098Source for Chinese
English prompts
Language
24th of 771,478
95% range 1,472 to 1,483
17,985Source for English prompts
French
Language
27th of 721,486
95% range 1,469 to 1,503
1,501Source for French
German
Language
24th of 551,470
95% range 1,448 to 1,491
750Source for German
Japanese
Language
35th of 541,421
95% range 1,395 to 1,448
515Source for Japanese
Korean
Language
28th of 541,426
95% range 1,402 to 1,450
657Source for Korean
Non-English prompts
Language
31st of 771,454
95% range 1,449 to 1,460
21,484Source for Non-English prompts
Russian
Language
36th of 771,459
95% range 1,450 to 1,469
4,341Source for Russian
Spanish
Language
20th of 701,473
95% range 1,455 to 1,491
1,296Source for Spanish
Entertainment, sport and media
Topic
37th of 771,436
95% range 1,428 to 1,443
8,466Source for Entertainment, sport and media
Law and government
Topic
37th of 761,468
95% range 1,457 to 1,479
3,130Source for Law and government
Medicine and health
Topic
16th of 751,487
95% range 1,476 to 1,499
2,908Source for Medicine and health
Science
Topic
26th of 771,483
95% range 1,475 to 1,492
6,388Source for Science
Software and IT
Topic
27th of 771,492
95% range 1,486 to 1,498
15,688Source 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
Baidu
Access, as listed by Epoch AI
Not stated
Licence, as listed by Arena
Proprietary
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. See models, apps and harnesses and how AI pricing works.

Price

Price not independently verified

We have not been able to check this maker's own pricing page, so we show nothing for it.

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 ERNIE 5.1. 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)
1,468
Arena score
95% range 1,463 to 1,472, 39,469 votes
Strong effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,441
Arena score
95% range 1,432 to 1,449, 6,445 votes
Strong effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,488
Arena score
95% range 1,481 to 1,495, 10,923 votes
Strong effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,482
Arena score
95% range 1,468 to 1,495, 1,985 votes
Strong effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,460
Arena score
95% range 1,454 to 1,467, 12,664 votes
Strong effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,473
Arena score
95% range 1,465 to 1,481, 7,814 votes
Top tier effort: not stated, bradley-terry rating ERNIE 5.1
lmarena · text/latest
28 Oct 2026 Source for ERNIE 5.1 Arena text: business and management score (lmarena)
Arena WebDev: building web appsNot enough data
FrontierMath Tiers 1-3 (v2)Not enough data
OTIS Mock AIME 2024-2025Not enough data
GPQA DiamondNot enough data
SimpleQA VerifiedNot enough data
SWE-bench Verified (Epoch runs)Not enough data
FrontierCode (reported by Cognition)Not enough data

Missing evidence

Not enough data for these tests:

  • Arena WebDev: building web apps
  • FrontierMath Tiers 1-3 (v2)
  • OTIS Mock AIME 2024-2025
  • GPQA Diamond
  • SimpleQA Verified
  • SWE-bench Verified (Epoch runs)
  • FrontierCode (reported by Cognition)

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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