Where it should be considered first
- 中文 workflows, especially where this agent shows its strongest language score.
- Extraction tasks where it is a reasonable first shortlist candidate.
- Standard-budget business automation candidates.
Qwen Main
Strong Chinese business language and structured extraction.
AlibabastandardArena #2
Preview evidence60 runs
- Provider
- Alibaba
- Exact model version
- Not measured
- Evaluation batch
- maa-preview-002
- Test date
- 2026-06-27
- Context window
- Not measured
- Tool mode
- disabled
- Pricing source
- Not measured
- Latency
- Not measured
Best fit
- 中文 workflows where the agent has its strongest language evidence.
- Extraction tasks as a first shortlist candidate against at least two alternatives.
- Quality-sensitive business pilots.
Not a fit for
- Critical-failure rate is 10%; do not fully automate refund, compliance, safety, or legal work first.
- Format pass is 100%; retest JSON, dates, and missing fields before extraction launch.
- Do not treat the current score as permanent after model, pricing, or tool changes.
Alternatives
Overall84
Pass rate93%
Critical10%
Format pass100%
Measured avg. cost$0.0118
LatencyNot measured
Review before production
- Review failure tags such as literal_translation, unnatural_japanese, unauthorized_credit before production use.
- Critical-failure rate is 10%; do not rely on the overall score alone for support, refund, or compliance workflows.
- Format pass rate is 100%; retest JSON and missing-field behavior before extraction use cases go live.
Compare next
Profile metrics
Overall score: 84 Win rate: 25% Pass rate: 93% Critical: 10% Format pass rate: 100% Average run cost: $0.0118
Common failure tags
literal_translationunnatural_japaneseunauthorized_credit
Language performance
| 中文 | 89 |
| English | 81 |
| 日本語 | 83 |
| Español | 81 |
Task type performance
| Support | 82 |
| Writing | 82 |
| Extraction | 88 |
Decision profile
How should this agent enter a real pilot?
Translate the score into practical selection guidance: fit, no-fit, pilot path, and task evidence.
- 中文 workflows where the agent has its strongest language evidence.
- Extraction tasks as a first shortlist candidate against at least two alternatives.
- Quality-sensitive business pilots.
- Critical-failure rate is 10%; do not fully automate refund, compliance, safety, or legal work first.
- Format pass is 100%; retest JSON, dates, and missing fields before extraction launch.
- Do not treat the current score as permanent after model, pricing, or tool changes.
- Prepare 20-50 real samples across normal, edge, and high-risk cases.
- Compare against one high-score candidate and one lower-cost candidate.
- Record repair time, failure tags, and unacceptable failures before expanding automation.
Recommended pilot path
- Use 20–50 real samples across normal, edge, and high-risk inputs.
- Keep at least one lower-cost comparator.
- Human-review every critical failure and high-risk output.
- Retest after model, prompt, tool, or business-policy changes.
Task evidence
Representative task evidence for this agent
中文 / ExtractionChinese Contract Field Extraction96 · hallucinated_signing_date中文 / ExtractionChinese Sales Call Summary96 · missed_buying_signal日本語 / ExtractionJapanese Product Specification Extraction91 · hallucinated_material中文 / SupportChinese Customer Complaint Triage85 · unsafe_refund_promise中文 / WritingChinese App Review Pain Point Summary85 · hallucinated_issue