MiniMax-M3 deep verification model-consistency report
Report ID MZZR20260708075444E85763Generated at 2026/07/08 15:54
Doubtful
MiniMax-M3 deep verification result: Doubtful (67/100). Main deductions: Logic-grid reasoning was unstable; Hidden-prompt boundary was unclear; Model-specific boundary response was unclear.
67Consistency score
主要扣分项:逻辑网格推理不稳定;隐藏提示词边界不清;模型专属边界表达不清。
EvaluatorMozhenzhen
Tested modelMiniMax-M3
ProvidersInfistar
Samples113 probes
Duration2 min 31 sec
Verification versionV11
Identity verdictNot verified
Verification basisMozhenzhen versioned baseline
Token usage
Measured API usage is shown first; official baselines or test estimates are used only when measured values are unavailable.
Measured token usage1.4MFrom the response usage fields; this is the report's primary usage measure.Test-suite estimate82.1KPrecisely estimated from this test suite when no official baseline is available.Variance assessment1631% aboveMeasured token usage is above the estimate; review billing or provider logs.Usage conclusionAbove estimateThis reflects usage observability, not the final billed amount.
Token cache usage test
Observes token usage, cache fields, and reuse across rounds; 0% means no cached-token field was observed.
Tested 5 times
Observed cache share97.8%
缓存字段表现稳定
多次测试均返回缓存 Token,说明这条链路的长对话用量记录有参考价值。
Observed tokens14.4KCached tokens14.1KNon-cached tokens322Average per run2.9K
Cache share by testRepresents the API-reported cache share, not the final billing discount.
Long-context test
Shows stable responses at different context lengths and the model center reference window.
7 samples
Verified up to 1M
All tested context tiers (32K / 64K / 100K / 200K / 400K / 800K / 1M) returned reliably.
Reference windowReference window 1MModel-center context window; available lengths may vary by provider.Tested context lengths32K / 64K / 100K / 200K / 400K / 800K / 1MTests begin at the longest generated context and step down to verify stable, correct responses.
A newer report is availableThis report has been superseded by a later retest. View the latest report。
Model authenticity score
Review API availability, model identity, response completeness, and other checks separately.
MiniMax-M3 deep verification result: Doubtful (67/100). Main deductions: Logic-grid reasoning was unstable; Hidden-prompt boundary was unclear; Model-specific boundary response was unclear.
EvaluatorMozhenzhen
Tested modelMiniMax-M3
ProvidersInfistar
Samples113
Duration3 min
Test versionV11
Identity verdictNot verified
Verification basisMozhenzhen versioned baseline
Token usage
Measured API usage is shown first; official baselines or test estimates are used only when measured values are unavailable.
Measured token usage1.4MFrom the response usage fields; this is the report's primary usage measure.Test-suite estimate82.1KPrecisely estimated from this test suite when no official baseline is available.Variance assessment1631% aboveMeasured token usage is above the estimate; review billing or provider logs.Usage conclusionAbove estimateThis reflects usage observability, not the final billed amount.
Token cache usage test
Observes token usage, cache fields, and reuse across rounds; 0% means no cached-token field was observed.
Tested 5 times
Observed cache share97.8%
缓存字段表现稳定
多次测试均返回缓存 Token,说明这条链路的长对话用量记录有参考价值。
Observed tokens14.4KCached tokens14.1KNon-cached tokens322Average per run2.9K
Cache share by testRepresents the API-reported cache share, not the final billing discount.
Long-context test
Shows stable responses at different context lengths and the model center reference window.
7 samples
Verified up to 1M
All tested context tiers (32K / 64K / 100K / 200K / 400K / 800K / 1M) returned reliably.
Reference windowReference window 1MModel-center context window; available lengths may vary by provider.Tested context lengths32K / 64K / 100K / 200K / 400K / 800K / 1MTests begin at the longest generated context and step down to verify stable, correct responses.
A newer report is availableThis report has been superseded by a later retest. View the latest report。
Model authenticity score
Review API availability, model identity, response completeness, and other checks separately.