Where it should be considered first
- English workflows, especially where this agent shows its strongest language score.
- Writing tasks where it is a reasonable first shortlist candidate.
- Standard-budget business automation candidates.
Grok Main
Fast outputs with higher variance on business constraints.
xAIstandardArena #2
Preview evidence60 runs
- Provider
- xAI
- 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
- English workflows where the agent has its strongest language evidence.
- Writing tasks as a first shortlist candidate against at least two alternatives.
- Quality-sensitive business pilots.
Not a fit for
- Critical-failure rate is 27%; do not fully automate refund, compliance, safety, or legal work first.
- Format pass is 78%; retest JSON, dates, and missing fields before extraction launch.
- Do not treat the current score as permanent after model, pricing, or tool changes.
Alternatives
Overall75
Pass rate37%
Critical27%
Format pass78%
Measured avg. cost$0.0121
LatencyNot measured
Review before production
- Review failure tags such as unsafe_refund_promise, unsupported_claim, invalid_json before production use.
- Critical-failure rate is 27%; do not rely on the overall score alone for support, refund, or compliance workflows.
- Format pass rate is 78%; retest JSON and missing-field behavior before extraction use cases go live.
Compare next
Profile metrics
Overall score: 75 Win rate: 0% Pass rate: 37% Critical: 27% Format pass rate: 78% Average run cost: $0.0121
Common failure tags
unsafe_refund_promiseunsupported_claiminvalid_json
Language performance
| 中文 | 74 |
| English | 79 |
| 日本語 | 74 |
| Español | 74 |
Task type performance
| Support | 75 |
| Writing | 77 |
| Extraction | 75 |
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.
- English workflows where the agent has its strongest language evidence.
- Writing tasks as a first shortlist candidate against at least two alternatives.
- Quality-sensitive business pilots.
- Critical-failure rate is 27%; do not fully automate refund, compliance, safety, or legal work first.
- Format pass is 78%; 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
English / ExtractionMeeting Notes Action Item Extraction80 · discussion_as_actionEnglish / WritingSaaS Landing Page Hero Rewrite79 · generic_ai_copyEnglish / SupportRefund Policy Boundary Reply79 · unsafe_refund_promiseEnglish / SupportEnglish Security Questionnaire Answer79 · unsupported_security_claim日本語 / WritingJapanese Business Email Politeness Rewrite79 · unnatural_japanese