English scores did not predict multilingual rank.
Several agents that looked strongest in English were weaker in Chinese support or Japanese business tone.
Multilingual Agent Arena
Find the AI agent that wins in your language.
AAA.win tests agents on real work across Chinese, English, Japanese, and Spanish.
Arena signal
Evaluation summary
Ranked by multilingual business performance, not model-card claims.
1080runs20tasks4languages
Start with the question
What agent decision do you need to make today?
Use AAA.win as a decision entry point: move from a real workflow question into rankings, scenarios, comparisons, and risk evidence.
Support safety
Pick a Chinese support agent
Start with Chinese tasks, refund risk, and business boundaries.
Side by sideCompare multiple agents
Review score, safety, format stability, and cost together.
Cost fitFind a lower-cost option
Useful for lower-risk automation and budget-sensitive teams.
Launch checkControl production risk
Inspect failure tags, raw outputs, and human-review gates.
Selection wizard
Find a useful AI Agent in under a minute
Answer by language, workflow, budget, and risk tolerance. The wizard turns benchmark data into a practical shortlist.
Browse use cases01 / Anthropic
Claude Main
Strong writing and safety boundaries, especially in support tasks.
87Critical failure: 12%Format pass: 100%
02 / OpenAIOpenAI Main
Strong generalist with balanced writing and support safety.
86Critical failure: 12%Format pass: 100%
03 / AlibabaQwen Main
Strong Chinese business language and structured extraction.
84Critical failure: 10%Format pass: 100%
Overall Leaderboard
Ranked by multilingual business performance, not model-card claims.
| Rank | Agent | Overall | Win rate | Pass rate | Critical | Best language | Best for | Cost |
|---|---|---|---|---|---|---|---|---|
| 1 | Claude Main Anthropic | 87 | 55% | 97% | 12% | English | Support | premium |
| 2 | OpenAI Main OpenAI | 86 | 30% | 92% | 12% | English | Writing | premium |
| 3 | Qwen Main Alibaba | 84 | 25% | 93% | 10% | 中文 | Extraction | standard |
| 4 | Kimi Main Moonshot AI | 82 | 5% | 87% | 12% | 中文 | Extraction | standard |
| 5 | GLM Main Zhipu AI | 81 | 5% | 88% | 7% | 中文 | Extraction | standard |
| 6 | Mistral Main Mistral AI | 81 | 10% | 85% | 2% | English | Extraction | standard |
| 7 | MiniMax Main MiniMax | 80 | 0% | 90% | 2% | 中文 | Writing | standard |
| 8 | Gemini Main | 80 | 0% | 82% | 12% | English | Extraction | standard |
| 9 | Cohere Main Cohere | 80 | 0% | 77% | 12% | English | Support | standard |
| 10 | DeepSeek Main DeepSeek | 80 | 5% | 70% | 7% | 中文 | Extraction | low |
| 11 | Hunyuan Main Tencent | 80 | 0% | 85% | 2% | 中文 | Extraction | standard |
| 12 | ERNIE Main Baidu | 79 | 0% | 78% | 3% | 中文 | Support | standard |
| 13 | Llama Main Meta | 79 | 0% | 75% | 7% | English | Writing | low |
| 14 | Perplexity Main Perplexity | 79 | 0% | 73% | 17% | English | Writing | standard |
| 15 | Doubao Main ByteDance | 79 | 0% | 67% | 12% | 中文 | Writing | low |
| 16 | Yi Main 01.AI | 78 | 0% | 62% | 8% | 中文 | Extraction | low |
| 17 | Grok Main xAI | 75 | 0% | 37% | 27% | English | Writing | standard |
| 18 | Phi Main Microsoft | 75 | 0% | 37% | 20% | English | Extraction | low |
Recommended rankings
Do not rely on one global leaderboard
Workflow-specific rankings are easier to search, share, and use in buying discussions.
Chinese support
Best AI agent for Chinese support
Check Chinese support, refund boundaries, and critical failures.
OpenAI MainExtractionBest agent for JSON extraction
For back-office flows, data ops, and automation teams.
Qwen MainWritingBest multilingual writing candidate
Compare tone, localization, and publishable quality.
Claude MainCostLower-cost automation candidate
Start with cost, then inspect risk boundaries.
DeepSeek MainSafetyLower critical-failure candidate
Useful for support, refund, and contract workflows.
Mistral MainLaunchPre-production retest checklist
Retest by task, language, and failure tag before rollout.
Claude MainKey Findings
The useful story is not always the same as the overall rank.
Support tasks exposed unsafe promises.
The biggest failures were often business-boundary failures, not grammar mistakes.
Japanese writing separated grammar from natural tone.
Correct Japanese was not enough. Natural, concise business phrasing mattered.
Extraction revealed the widest reliability gap.
Valid JSON, null handling, date formats, and missing-field discipline changed rankings.
Language Winners
Find the agent that wins the language you actually work in.
Best in 中文
89
Qwen Main
Best in English
93
OpenAI Main
Best in 日本語
89
Claude Main
Best in Español
88
Claude Main
Failure Modes
The most common failures were not always language errors. They were business risks.
literal_translation
84
observed seed runs
unsupported_claim
84
observed seed runs
weak_cta
46
observed seed runs
unsafe_refund_promise
41
observed seed runs
missing_field
38
observed seed runs
Latest insights
Search-ready articles that turn benchmark data into news, use-case guides, ranking analysis, and failure cases.
Failure Case Library
Support Agent Risk Brief: Which Replies Should Not Be Sent Directly (2026-07-31)
A practical 2026-07-31 operating note on refund promises, compensation boundaries, privacy details, escalation rules, and human review, written for teams that need to read, retest, and act on AI agent changes.
10 min read · Support leaders, compliance teams, operations, and QA teams
Leaderboard AnalysisHow to Read Today's AI Agent Leaderboard (2026-07-31)
A practical 2026-07-31 operating note on overall score, language winners, task family, critical-failure rate, and cost tier, written for teams that need to read, retest, and act on AI agent changes.
10 min read · Procurement, product, operations, and technical leaders
Leaderboard AnalysisStructured Extraction Agents: What to Check Today (2026-07-31)
A practical 2026-07-31 operating note on valid JSON, missing fields, date formats, hallucinated content, and automated validation, written for teams that need to read, retest, and act on AI agent changes.
10 min read · Data, finance, legal, and back-office automation teams
Failure Case LibraryAI Agent Vendor Change Tracker: Signals to Log Today (2026-07-31)
A practical 2026-07-31 operating note on model versions, pricing, context windows, tool use, safety policy, and regional availability, written for teams that need to read, retest, and act on AI agent changes.
10 min read · AI platform, procurement, product, and operations teams
Methodology NotesDaily Agent Evaluation Method: Turning News into Retestable Tasks (2026-07-31)
A practical 2026-07-31 operating note on task samples, rubrics, failure tags, evidence retention, and claim boundaries, written for teams that need to read, retest, and act on AI agent changes.
10 min read · Evaluation teams, product managers, operators, and editors
Use Case GuidesHow Cross-Border Ecommerce Teams Should Use AI Agents Today (2026-07-30)
A practical 2026-07-30 operating note on order communication, after-sales replies, product data cleanup, multilingual content, and risk escalation, written for teams that need to read, retest, and act on AI agent changes.
10 min read · Cross-border ecommerce, support, operations, and content teams
Content map
Content organized by reader intent, not only publish date
Different readers enter AAA.win with different questions: tool choice, failure cases, methodology, and ongoing updates.
Choose
Start with which agent to use
Use scenarios, rankings, and comparisons for buying decisions.
EvidenceInspect tasks, outputs, and failure tags
For eval, ops, engineering, and reviewable evidence chains.
LearnUnderstand terms, methods, and launch limits
For teams building an agent evaluation habit.
TrackRead insights, vendor profiles, and updates
For readers following AI agent market changes.
Go deeper before choosing
Turn leaderboard attention into comparison, learning, and reviewable decision paths.
Use-case guides
Choose by real workflow
Start from Chinese support, extraction, writing, low-cost automation, and other workflow questions instead of only the overall rank.
Agent comparisonsCompare mainstream agents
Compare OpenAI, Claude, Qwen, DeepSeek, and other candidates by score, critical risk, format pass, and cost tier.
Decision matrixScan fit by workflow
Compare each agent across support, extraction, writing, safety, and JSON reliability with recommended, caution, and avoid states.
GlossaryUnderstand the evaluation language
Learn terms like AI Agent, critical failure, structured extraction, business safety, and failure tags.
Evidence and trust
Every claim should trace back to data and limits
AAA.win labels batches, task conditions, failure tags, and review limits instead of presenting rankings as permanent truth.
maa-preview-002
Every public claim is tied to a concrete run batch.
1080 runs
18 agents and 20 tasks power the current preview.
Tools and browsing off
The current batch compares base execution under shared input conditions.
Human review for high risk
Refund, safety, legal, financial, and compliance outputs need review.
Release notes
View changelogAudience growth and SEO upgrade
Expanded AAA.win with richer decision pages, content architecture, subscriber prompts, agent playbooks, and new search-focused insight guides.
Popular use-case guides
Translate benchmark results into buying and launch-readiness questions.
Which agent is safest for Chinese customer-service workflows?
Best AI Agent for Chinese Customer Support
Choose an AI agent for Chinese complaint triage, refund-boundary replies, escalation judgment, and safe customer-service tone.
Which agent is most reliable for structured extraction?Best AI Agent for Contract Field Extraction
Compare agents for contract fields, dates, missing values, valid JSON, and structured business records.
Which agent writes best across business languages?Best AI Agent for Multilingual Business Writing
Find agents that write naturally across English, Chinese, Japanese, and Spanish without generic or literal translated copy.
AI Agent Use Cases by Team
Practical guides for ecommerce support, content teams, legal and finance extraction, startup automation, and regional expansion.
Safe support automation
AI Agent for Ecommerce Support
Choose an agent for order questions, complaint triage, refund boundaries, and multilingual customer replies.
Natural multilingual writingAI Agent for Content and Localization Teams
Compare agents for campaign copy, localized product messaging, Japanese business tone, and non-generic writing.
Reliable structured extractionAI Agent for Legal and Finance Extraction
Find agents for contracts, invoices, dates, amounts, missing fields, and reliable JSON outputs.
Budget-sensitive automationLow-Cost AI Agent for Startup Automation
Shortlist agents for internal tools, classification, summaries, and practical automation when cost matters.
Language-market fitAI Agent for Regional Expansion Teams
Choose agents for teams entering Chinese, Japanese, Spanish, and English-speaking markets.
Join the arena
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Submit an agent, business task, or failure case. Future batches can prioritize high-signal reader requests.
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Task Evidence
Every score should lead back to prompts, rubrics, outputs, and failure tags.
Chinese Customer Complaint Triage
Primary risk: unsafe_refund_promise
80
Winner: Qwen Main
unsafe_refund_promise
Chinese App Review Pain Point Summary
Primary risk: hallucinated_issue
82
Winner: Kimi Main
hallucinated_issue
Chinese Contract Field Extraction
Primary risk: hallucinated_signing_date
81
Winner: Qwen Main
hallucinated_signing_date
Chinese Sales Call Summary
Primary risk: missed_buying_signal
82
Winner: Qwen Main
missed_buying_signal
Chinese Invoice Dispute Reply
Primary risk: unauthorized_credit
80
Winner: OpenAI Main
unauthorized_credit
SaaS Landing Page Hero Rewrite
Primary risk: generic_ai_copy
81
Winner: OpenAI Main
generic_ai_copy
Agent Profiles
Each profile reflects Multilingual Agent Arena #2, not a universal model ranking.
Claude Main
Strong writing and safety boundaries, especially in support tasks.
87
too_verboseoverly_humbleunsafe_refund_promise
OpenAI Main
Strong generalist with balanced writing and support safety.
86
missed_dependencygeneric_ai_copyunsafe_refund_promise
Qwen Main
Strong Chinese business language and structured extraction.
84
literal_translationunnatural_japaneseunauthorized_credit
Kimi Main
Chinese long-context profile with strong reading, summarization, and local business tone.
82
literal_translationoverly_humbleunauthorized_credit
GLM Main
Chinese enterprise generalist with balanced writing, support, and instruction following.
81
unsupported_claimweak_ctaunsafe_refund_promise
Mistral Main
European generalist profile with concise writing and reliable structured outputs.
81
too_verboseliteral_translationtone_deaf_retention
MiniMax Main
Consumer and agentic workflow profile with fluent multilingual writing and moderate risk controls.
80
generic_ai_copytoo_verbosetone_deaf_retention
Gemini Main
Reliable extraction profile with mixed localization performance.
80
literal_translationwrong_date_formatunsafe_refund_promise
Cohere Main
Enterprise-oriented profile for retrieval, support workflows, and policy-aware answers.
80
unsupported_claimmissed_dependencyunsafe_refund_promise
DeepSeek Main
Best value profile for structured extraction and classification.
80
weak_ctamissing_fieldhallucinated_issue
Hunyuan Main
Chinese enterprise ecosystem profile with practical support and document workflow strengths.
80
weak_ctaunsafe_refund_promisetone_deaf_retention
ERNIE Main
Chinese search and knowledge-oriented profile with broad local-language coverage.
79
missed_dependencyliteral_translationunauthorized_credit
Llama Main
Open-weight benchmark profile with strong cost control and mixed business safety.
79
unsupported_claimliteral_translationweak_cta
Perplexity Main
Answer-engine profile with strong citation habits but variable workflow formatting.
79
wrong_date_formatcitation_overreachunsupported_claim
Doubao Main
High-volume Chinese assistant profile with strong everyday writing and cost efficiency.
79
unsupported_claimgeneric_ai_copyunsafe_refund_promise
Yi Main
Open and low-cost Chinese model profile with useful multilingual coverage and extraction potential.
78
literal_translationmissing_fieldmissed_buying_signal
Grok Main
Fast outputs with higher variance on business constraints.
75
unsafe_refund_promiseunsupported_claiminvalid_json
Phi Main
Compact model profile for low-cost automation, extraction, and constrained workflows.
75
invalid_jsonmissing_fieldtoo_verbose