GLM · Last 7 days

GLM 5.2

0–100 · higher means more positive community experience, not benchmark performance.

Updated 2026-10-03 20:52 UTC · 2026-09-26 – 2026-10-03 UTC
All-platform score69.1/10020 comments in 7 days

Discussion overview

What the full sample discusses

All platforms · 20 eligible comments over 7 days, including usage-limit feedback; deduplicated by source and comment.

  • General text · 12 comments: 10 positive / 2 negative / 0 mixed or neutral
  • Reasoning · 5 comments: 3 positive / 2 negative / 0 mixed or neutral
  • Coding · 1 comments: 1 positive / 0 negative / 0 mixed or neutral
  • Local deploy · 1 comments: 1 positive / 0 negative / 0 mixed or neutral

Comments may cover multiple dimensions; counts are not additive or equivalent to the weighted score. Links show selected source excerpts.

Recent change

Rolling 7-day score: +7.7 points vs 7 days ago. Discussion mix can affect scores; this does not establish a cause.

Source coverage and discussion concentration

Hacker News 5 · Reddit 7 · Zhihu 8

9 identifiable discussions cover 15/20 comments; the largest has 6. Remaining thread identities are unknown; this is not a count of independent users.

Selected individual opinions

Explore individual experiences below, filtered by category and sentiment.

About the sample and scores

As of 2026-10-03 20:52:04 UTC, GLM 5.2 in the GLM family has 20 explicitly attributed community comments in the last 7 days; its community score is 69.1/100. Available category scores include General text 69.6/100 (n=12); Reasoning 52.9/100 (n=5). Scoring method and sources

RECENT EXPERIENCE

How the Experience Index is changing

−1.3vs 7 days ago · points

30 days of rolling 7-day scores at each daily snapshot. The vertical scale adapts to the data. Missing or insufficient samples leave gaps; today is still updating.

Tap or use ← → for dates, scores and sample sizes. Blank dates have insufficient data.

GLM 5.2 · Reddit · 30 days of rolling 7-day experience scores 4050607080 Observed-day mean: 63.9 2026-09-04 · 67.6 · n=29 · 2026-08-28T23:00:03+00:00 – 2026-09-04T23:00:03+00:002026-09-05 · 67.1 · n=31 · 2026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:002026-09-06 · 69.0 · n=28 · 2026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:002026-09-07 · 71.9 · n=28 · 2026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:002026-09-08 · 72.9 · n=32 · 2026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:002026-09-09 · 73.8 · n=33 · 2026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:002026-09-10 · 76.8 · n=33 · 2026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:002026-09-11 · 74.7 · n=25 · 2026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:002026-09-12 · 72.6 · n=27 · 2026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:002026-09-13 · 71.8 · n=26 · 2026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:002026-09-14 · 72.9 · n=32 · 2026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:002026-09-15 · 69.8 · n=29 · 2026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:002026-09-16 · 62.9 · n=28 · 2026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:002026-09-17 · 63.7 · n=27 · 2026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:002026-09-18 · 63.9 · n=26 · 2026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:002026-09-19 · 64.5 · n=23 · 2026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:002026-09-20 · 66.3 · n=24 · 2026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:002026-09-21 · 64.5 · n=26 · 2026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:002026-09-22 · 64.9 · n=20 · 2026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:002026-09-23 · 63.6 · n=21 · 2026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:002026-09-24 · 62.1 · n=20 · 2026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:002026-09-25 · 58.5 · n=17 · 2026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:002026-09-26 · 59.3 · n=18 · 2026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:002026-09-27 · 51.8 · n=16 · 2026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:002026-09-28 · 41.3 · n=7 · 2026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:002026-09-29 · 49.0 · n=10 · 2026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:002026-09-30 · 50.1 · n=9 · 2026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:002026-10-01 · 51.8 · n=10 · 2026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:002026-10-02 · 59.8 · n=7 · 2026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:002026-10-03 · 58.0 · n=6 · 2026-09-26T20:52:04+00:00 – 2026-10-03T20:52:04+00:00 58.0 09-0409-1209-1909-2610-03 GLM 5.2 · Reddit · 30 days of rolling 7-day experience scores 4050607080 Observed-day mean: 63.9 2026-09-04 · 67.6 · n=29 · 2026-08-28T23:00:03+00:00 – 2026-09-04T23:00:03+00:002026-09-05 · 67.1 · n=31 · 2026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:002026-09-06 · 69.0 · n=28 · 2026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:002026-09-07 · 71.9 · n=28 · 2026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:002026-09-08 · 72.9 · n=32 · 2026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:002026-09-09 · 73.8 · n=33 · 2026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:002026-09-10 · 76.8 · n=33 · 2026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:002026-09-11 · 74.7 · n=25 · 2026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:002026-09-12 · 72.6 · n=27 · 2026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:002026-09-13 · 71.8 · n=26 · 2026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:002026-09-14 · 72.9 · n=32 · 2026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:002026-09-15 · 69.8 · n=29 · 2026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:002026-09-16 · 62.9 · n=28 · 2026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:002026-09-17 · 63.7 · n=27 · 2026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:002026-09-18 · 63.9 · n=26 · 2026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:002026-09-19 · 64.5 · n=23 · 2026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:002026-09-20 · 66.3 · n=24 · 2026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:002026-09-21 · 64.5 · n=26 · 2026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:002026-09-22 · 64.9 · n=20 · 2026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:002026-09-23 · 63.6 · n=21 · 2026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:002026-09-24 · 62.1 · n=20 · 2026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:002026-09-25 · 58.5 · n=17 · 2026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:002026-09-26 · 59.3 · n=18 · 2026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:002026-09-27 · 51.8 · n=16 · 2026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:002026-09-28 · 41.3 · n=7 · 2026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:002026-09-29 · 49.0 · n=10 · 2026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:002026-09-30 · 50.1 · n=9 · 2026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:002026-10-01 · 51.8 · n=10 · 2026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:002026-10-02 · 59.8 · n=7 · 2026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:002026-10-03 · 58.0 · n=6 · 2026-09-26T20:52:04+00:00 – 2026-10-03T20:52:04+00:00 58.0 09-0409-1209-1909-2610-03
Daily readings & sample sizes
DateScorenScoring window (UTC)
2026-10-0358.062026-09-26T20:52:04+00:00 – 2026-10-03T20:52:04+00:00
2026-10-0259.872026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:00
2026-10-0151.8102026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:00
2026-09-3050.192026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:00
2026-09-2949.0102026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:00
2026-09-2841.372026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:00
2026-09-2751.8162026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:00
2026-09-2659.3182026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:00
2026-09-2558.5172026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:00
2026-09-2462.1202026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:00
2026-09-2363.6212026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:00
2026-09-2264.9202026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:00
2026-09-2164.5262026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:00
2026-09-2066.3242026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:00
2026-09-1964.5232026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:00
2026-09-1863.9262026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:00
2026-09-1763.7272026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:00
2026-09-1662.9282026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:00
2026-09-1569.8292026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:00
2026-09-1472.9322026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:00
2026-09-1371.8262026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:00
2026-09-1272.6272026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:00
2026-09-1174.7252026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:00
2026-09-1076.8332026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:00
2026-09-0973.8332026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:00
2026-09-0872.9322026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:00
2026-09-0771.9282026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:00
2026-09-0669.0282026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:00
2026-09-0567.1312026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:00
2026-09-0467.6292026-08-28T23:00:03+00:00 – 2026-09-04T23:00:03+00:00

Reddit · 58.0 · 6 scored comments · Read platform reviews →

ONE MODEL, DIFFERENT COMMUNITIES

Across the communities

Last 7 days

Scored separately for each platform, with different samples and audiences. Platform scores are not simply averaged; scored counts exclude quota-only comments.

Scores range from 0 to 100. Select a platform for its trend and reviews. Latest opinion time is not crawler health.

Community reviews

Selected comments from the last 7 days. The balance of excerpts does not represent the share of positive reviews.

0 selected excerpts

Community reports about limits cannot establish official allowances.

No selected comments for this filter in the last 7 days.

Explore long-term changes & analysis

Model lifecycle

GLM 5.2

Released 2026-06-16 · Back to GLM

Exact-version signals observed 2026-09-23–2026-10-02 · n=23

Data window: 2026-09-05 00:00:00 to 2026-10-03 00:00:00 UTC · Scoring method: experience_score_v3.

Insufficient historical baseline The original baseline window lacks enough current-method evidence for a long-term comparison.

Lifecycle updated daily · latest complete UTC day 2026-10-02

The current classification method has insufficient evidence in the original baseline window. The window is preserved; no long-term improvement or decline is inferred, and old-method scores are not compared.

Fixed 14-day baseline
–
n=0
Latest 28 days
–
n=22
Change vs baseline
–
90-day slope
–
pts / 30 days

14-day rolling experience

Each daily point summarizes the previous 14 complete UTC days. The dashed line is the fixed release baseline; the verdict still uses independent non-overlapping 14-day segments.

–

0 of 4 independent 14-day segments ready for trend judgment.

What explains the change

Experience change and discussion-mix change are separated. These are observational contributions, not proof of cause.

No category has enough samples in both windows for a contribution conclusion.

Category Baseline → current Category change Weight share Experience contribution Discussion-mix contribution
Coding Baseline → currentnot enough datan=0 → 1 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Image generation Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Image understanding Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Local deploy Baseline → currentnot enough datan=0 → 2 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Reasoning Baseline → currentnot enough datan=0 → 6 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Roleplay / creative Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Safety & refusals Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Speed & latency Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
General text Baseline → currentnot enough datan=0 → 13 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Video generation Baseline → currentnot enough datan=0 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–

Lifecycle scores use the same experience-signal weights as the main index, without sample shrinkage after n=30. They measure public user perception, not model capability or backend causes.

How's your AI experience today?