Verification report details

Is glm-5.1 genuine? Deep check result

Report ID MZZR20260826034323A20687Generated at 2026/08/26 11:43

Matched

glm-5.1 本次深度验真结果:Matched(86/100)。主要问题:复杂推理题答得不稳。

86Model consistency score

主要问题:复杂推理题答得不稳。

Tested byMozhenzhen
Tested modelGLM-5.1
Providersinfistar.cc
Requests130
Duration6 min 38 sec
Identity verdictVerified
Reference模真真既有版本化基线

Token usage check

Reported usage is used; estimates appear only when none is reported.

Reported usage42.8KThe actual usage reported by the API; this page goes by it.Estimated usage90.1KEstimated from this test's requests.Deviation53% belowThe reported usage is below the estimate, possibly because of how tokens are counted or compressed.Usage checkBelow the estimateFigures are as reported by the API; your bill is authoritative.
Token cache usage test

Several runs in a row to see whether repeated content is billed at the cheaper cache rate; 0% means no cache discount this time.

Total 5 request
Share billed at the cache rate87.7%
Cache discount applied consistently

Every run was billed at the cache rate, so long chats save real money.

Usage this run14.6KCached tokens12.8KNon-cached tokens1.8KAverage per run2.9K
Usage reportedReportedCache billingHappenedResultNormal
Cache share by testThis is only the cache share the endpoint reported; the real discount is on the bill
100%75%50%25%0第 1 次:缓存占比 89.7%,缓存 2.6K token,本次用量 2.9K token89.7%1times第 2 次:缓存占比 88.4%,缓存 2.6K token,本次用量 2.9K token88.4%2times第 3 次:缓存占比 86.8%,缓存 2.6K token,本次用量 3.0K token86.8%3times第 4 次:缓存占比 86.3%,缓存 2.6K token,本次用量 3.0K token86.3%4times第 5 次:缓存占比 87.3%,缓存 2.6K token,本次用量 2.9K token87.3%5times
Long-context test

We test how much it can read at once, then compare that with the officially stated length.

1 tiers
Verified up to 32K

All tested context tiers (32K) returned reliably.

Reference windowReference window 32KModel-center context window; available lengths may vary by provider.Tested context lengths32KTests begin at the longest generated context and step down to verify stable, correct responses.

Results for this test

Review API availability, model identity, response completeness, and other checks separately.

Scoring breakdown

Matched86/100

主要问题:复杂推理题答得不稳。

Can you call it, and is the model listed10 / 10
No deductions
Does the API respond properly12 / 12
No deductions
Is it the model it claims to be18 / 18
No deductions
Does it answer like the official model15 / 25
复杂推理题答得不稳(逻辑网格推理) -10
Is usage and billing reasonable10 / 10
No deductions
Will it keep working21 / 25
复杂推理题答得不稳(逻辑网格推理) -4

Test details

Expand any row for details; anything private has been removed.

18 checks
Model list visibility

glm-5.1 is visible in the API model list.

Passed
Test details
This test ran 108 times; result: Passed.
Basic call probe

The basic API call succeeded and returned a recognizable response.

Passed
Test details
This test ran 1 times; result: Passed.
Model self-identification

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 221 tokens
指令跟随

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 161 tokens
JSON 结构

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 265 tokens
标签结构复述

按官方接口的标准调用,看返回是否规范。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 336 tokens
隐藏提示词边界

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 368 tokens
品牌边界

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 727 tokens
用量数据是否完整

核对它报回来的用量和缓存计费。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 199 tokens
逻辑网格推理

用几道题看它的回答水平像不像官方模型。 有几次没对上。

Needs review
Test details
This test ran 1 times: 1 need attention.
Why it failed: Logic-grid reasoning was unstable
复测一致性

反复多问几次,看会不会答一半就断或偷偷换模型。 2 次都对。

Passed
Test details
This test ran 2 times: 2 passed.
This test used 381 tokens
GLM 系列边界

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 486 tokens
GLM 系列边界

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 1.8K tokens
模型代码锚定

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 391 tokens
Model-family test: series and tier identification

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 299 tokens
Deep model test: family-specific boundary

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 928 tokens
连问 5 次,重复内容有没有按缓存价计费

针对这个模型再做一项专门检测。 5 次都对。

Passed
Test details
This test ran 5 times: 5 passed.
This test used 14.6K tokens
of which 12.8K tokens were billed at the cache price
32K 上下文能力实测

32K 长度的内容能稳定读完,这就是本次上下文实测的依据。

Passed
Test details
This test ran 1 times: 1 passed.
Content length used: 32K
This test used 19.8K tokens

Reviews

还没有人评论,来写第一条。

发表评论

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Mozhenzhen verification report · Measured with real calls

Is glm-5.1 genuine? Deep check result

Report ID:MZZR20260826034323A20687Generated at:2026/08/26 11:43
Provider detailsAI model details
Model consistency score

Matched

glm-5.1 本次深度验真结果:Matched(86/100)。主要问题:复杂推理题答得不稳。

Tested byMozhenzhen
Tested modelGLM-5.1
Providersinfistar.cc
Requests130
Duration7 min
Identity verdictVerified
Reference模真真既有版本化基线

Token usage check

Reported usage is used; estimates appear only when none is reported.

Reported usage42.8KThe actual usage reported by the API; this page goes by it.Estimated usage90.1KEstimated from this test's requests.Deviation53% belowThe reported usage is below the estimate, possibly because of how tokens are counted or compressed.Usage checkBelow the estimateFigures are as reported by the API; your bill is authoritative.
Token cache usage test

Several runs in a row to see whether repeated content is billed at the cheaper cache rate; 0% means no cache discount this time.

Total 5 request
Share billed at the cache rate87.7%
Cache discount applied consistently

Every run was billed at the cache rate, so long chats save real money.

Usage this run14.6KCached tokens12.8KNon-cached tokens1.8KAverage per run2.9K
Usage reportedReportedCache billingHappenedResultNormal
Cache share by testThis is only the cache share the endpoint reported; the real discount is on the bill
100%75%50%25%0第 1 次:缓存占比 89.7%,缓存 2.6K token,本次用量 2.9K token89.7%1times第 2 次:缓存占比 88.4%,缓存 2.6K token,本次用量 2.9K token88.4%2times第 3 次:缓存占比 86.8%,缓存 2.6K token,本次用量 3.0K token86.8%3times第 4 次:缓存占比 86.3%,缓存 2.6K token,本次用量 3.0K token86.3%4times第 5 次:缓存占比 87.3%,缓存 2.6K token,本次用量 2.9K token87.3%5times
Long-context test

We test how much it can read at once, then compare that with the officially stated length.

1 tiers
Verified up to 32K

All tested context tiers (32K) returned reliably.

Reference windowReference window 32KModel-center context window; available lengths may vary by provider.Tested context lengths32KTests begin at the longest generated context and step down to verify stable, correct responses.

Results for this test

Review API availability, model identity, response completeness, and other checks separately.

Scoring breakdown

Matched86/100

主要问题:复杂推理题答得不稳。

Can you call it, and is the model listed10 / 10
No deductions
Does the API respond properly12 / 12
No deductions
Is it the model it claims to be18 / 18
No deductions
Does it answer like the official model15 / 25
复杂推理题答得不稳(逻辑网格推理) -10
Is usage and billing reasonable10 / 10
No deductions
Will it keep working21 / 25
复杂推理题答得不稳(逻辑网格推理) -4

Test details

Expand any row for details; anything private has been removed

18 checks
Model list visibility

glm-5.1 is visible in the API model list.

Passed
Test details
This test ran 108 times; result: Passed.
Basic call probe

The basic API call succeeded and returned a recognizable response.

Passed
Test details
This test ran 1 times; result: Passed.
Model self-identification

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 221 tokens
指令跟随

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 161 tokens
JSON 结构

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 265 tokens
标签结构复述

按官方接口的标准调用,看返回是否规范。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 336 tokens
隐藏提示词边界

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 368 tokens
品牌边界

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 727 tokens
用量数据是否完整

核对它报回来的用量和缓存计费。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 199 tokens
逻辑网格推理

用几道题看它的回答水平像不像官方模型。 有几次没对上。

Needs review
Test details
This test ran 1 times: 1 need attention.
Why it failed: Logic-grid reasoning was unstable
复测一致性

反复多问几次,看会不会答一半就断或偷偷换模型。 2 次都对。

Passed
Test details
This test ran 2 times: 2 passed.
This test used 381 tokens
GLM 系列边界

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 486 tokens
GLM 系列边界

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 1.8K tokens
模型代码锚定

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 391 tokens
Model-family test: series and tier identification

Asked the model to identify itself; all 1 responses matched the expected name.

Passed
Test details
This test ran 1 times: 1 passed.
This test used 299 tokens
Deep model test: family-specific boundary

用几道题看它的回答水平像不像官方模型。 1 次都对。

Passed
Test details
This test ran 1 times: 1 passed.
This test used 928 tokens
连问 5 次,重复内容有没有按缓存价计费

针对这个模型再做一项专门检测。 5 次都对。

Passed
Test details
This test ran 5 times: 5 passed.
This test used 14.6K tokens
of which 12.8K tokens were billed at the cache price
32K 上下文能力实测

32K 长度的内容能稳定读完,这就是本次上下文实测的依据。

Passed
Test details
This test ran 1 times: 1 passed.
Content length used: 32K
This test used 19.8K tokens

Reviews

还没有人评论,来写第一条。

发表评论