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GPT · Last 7 days

GPT-5.6 Luna

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

Updated 2026-10-04 08:32 UTC · 2026-09-27 – 2026-10-04 UTC
All-platform score60.2/10030 comments in 7 days

Discussion overview

What the full sample discusses

All platforms · 30 eligible comments over 7 days, including usage-limit feedback; deduplicated by source and comment.

  • General text · 10 comments: 6 positive / 4 negative / 0 mixed or neutral
  • Usage limits · 8 comments: 5 positive / 2 negative / 1 mixed or neutral
  • Reasoning · 6 comments: 4 positive / 2 negative / 0 mixed or neutral
  • Coding · 4 comments: 3 positive / 1 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: +12.8 points vs 7 days ago. Discussion mix can affect scores; this does not establish a cause.

Source coverage and discussion concentration

Hacker News 3 · Reddit 21 · Zhihu 6

21 identifiable discussions cover 27/30 comments; the largest has 3. Remaining thread identities are unknown; this is not a count of independent users.

Selected individual opinions

One user feels that the quota of ChatGPT's free model 5.6 Luna is relatively sufficient One user reported that GPT-5.6 Luna was extremely unintelligent, unable to use tool calls, and shockingly poor in chat.

About the sample and scores

As of 2026-10-04 08:32:03 UTC, GPT-5.6 Luna in the GPT family has 30 explicitly attributed community comments in the last 7 days; its community score is 60.2/100. Available category scores include General text 56.5/100 (n=10); Reasoning 57.8/100 (n=6); Usage limits 59.1/100 (n=8). Scoring method and sources

RECENT EXPERIENCE

How the Experience Index is changing

+12.8vs 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.

GPT-5.6 Luna · All platforms · 30 days of rolling 7-day experience scores 4050607080 Observed-day mean: 60.7 2026-09-05 · 50.6 · n=21 · 2026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:002026-09-06 · 57.0 · n=19 · 2026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:002026-09-07 · 64.2 · n=19 · 2026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:002026-09-08 · 63.8 · n=22 · 2026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:002026-09-09 · 62.2 · n=18 · 2026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:002026-09-10 · 67.0 · n=20 · 2026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:002026-09-11 · 71.0 · n=20 · 2026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:002026-09-12 · 74.4 · n=22 · 2026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:002026-09-13 · 72.5 · n=23 · 2026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:002026-09-14 · 66.0 · n=25 · 2026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:002026-09-15 · 67.1 · n=23 · 2026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:002026-09-16 · 72.4 · n=29 · 2026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:002026-09-17 · 68.6 · n=27 · 2026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:002026-09-18 · 68.8 · n=27 · 2026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:002026-09-19 · 69.0 · n=26 · 2026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:002026-09-20 · 70.6 · n=25 · 2026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:002026-09-21 · 52.5 · n=31 · 2026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:002026-09-22 · 54.9 · n=39 · 2026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:002026-09-23 · 48.3 · n=49 · 2026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:002026-09-24 · 51.3 · n=59 · 2026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:002026-09-25 · 50.2 · n=63 · 2026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:002026-09-26 · 48.6 · n=67 · 2026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:002026-09-27 · 47.4 · n=77 · 2026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:002026-09-28 · 55.8 · n=64 · 2026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:002026-09-29 · 54.6 · n=62 · 2026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:002026-09-30 · 58.4 · n=51 · 2026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:002026-10-01 · 55.4 · n=40 · 2026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:002026-10-02 · 57.2 · n=36 · 2026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:002026-10-03 · 60.8 · n=31 · 2026-09-26T23:57:02+00:00 – 2026-10-03T23:57:02+00:002026-10-04 · 60.2 · n=30 · 2026-09-27T08:32:03+00:00 – 2026-10-04T08:32:03+00:00 60.2 09-0509-1309-2009-2710-04 GPT-5.6 Luna · All platforms · 30 days of rolling 7-day experience scores 4050607080 Observed-day mean: 60.7 2026-09-05 · 50.6 · n=21 · 2026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:002026-09-06 · 57.0 · n=19 · 2026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:002026-09-07 · 64.2 · n=19 · 2026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:002026-09-08 · 63.8 · n=22 · 2026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:002026-09-09 · 62.2 · n=18 · 2026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:002026-09-10 · 67.0 · n=20 · 2026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:002026-09-11 · 71.0 · n=20 · 2026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:002026-09-12 · 74.4 · n=22 · 2026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:002026-09-13 · 72.5 · n=23 · 2026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:002026-09-14 · 66.0 · n=25 · 2026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:002026-09-15 · 67.1 · n=23 · 2026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:002026-09-16 · 72.4 · n=29 · 2026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:002026-09-17 · 68.6 · n=27 · 2026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:002026-09-18 · 68.8 · n=27 · 2026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:002026-09-19 · 69.0 · n=26 · 2026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:002026-09-20 · 70.6 · n=25 · 2026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:002026-09-21 · 52.5 · n=31 · 2026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:002026-09-22 · 54.9 · n=39 · 2026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:002026-09-23 · 48.3 · n=49 · 2026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:002026-09-24 · 51.3 · n=59 · 2026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:002026-09-25 · 50.2 · n=63 · 2026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:002026-09-26 · 48.6 · n=67 · 2026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:002026-09-27 · 47.4 · n=77 · 2026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:002026-09-28 · 55.8 · n=64 · 2026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:002026-09-29 · 54.6 · n=62 · 2026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:002026-09-30 · 58.4 · n=51 · 2026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:002026-10-01 · 55.4 · n=40 · 2026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:002026-10-02 · 57.2 · n=36 · 2026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:002026-10-03 · 60.8 · n=31 · 2026-09-26T23:57:02+00:00 – 2026-10-03T23:57:02+00:002026-10-04 · 60.2 · n=30 · 2026-09-27T08:32:03+00:00 – 2026-10-04T08:32:03+00:00 60.2 09-0509-1309-2009-2710-04
Daily readings & sample sizes
DateScorenScoring window (UTC)
2026-10-0460.2302026-09-27T08:32:03+00:00 – 2026-10-04T08:32:03+00:00
2026-10-0360.8312026-09-26T23:57:02+00:00 – 2026-10-03T23:57:02+00:00
2026-10-0257.2362026-09-25T23:57:03+00:00 – 2026-10-02T23:57:03+00:00
2026-10-0155.4402026-09-24T23:57:02+00:00 – 2026-10-01T23:57:02+00:00
2026-09-3058.4512026-09-23T23:57:03+00:00 – 2026-09-30T23:57:03+00:00
2026-09-2954.6622026-09-22T23:57:03+00:00 – 2026-09-29T23:57:03+00:00
2026-09-2855.8642026-09-21T23:57:03+00:00 – 2026-09-28T23:57:03+00:00
2026-09-2747.4772026-09-20T23:57:03+00:00 – 2026-09-27T23:57:03+00:00
2026-09-2648.6672026-09-19T23:57:03+00:00 – 2026-09-26T23:57:03+00:00
2026-09-2550.2632026-09-18T23:57:03+00:00 – 2026-09-25T23:57:03+00:00
2026-09-2451.3592026-09-17T23:57:03+00:00 – 2026-09-24T23:57:03+00:00
2026-09-2348.3492026-09-16T23:57:03+00:00 – 2026-09-23T23:57:03+00:00
2026-09-2254.9392026-09-15T23:57:03+00:00 – 2026-09-22T23:57:03+00:00
2026-09-2152.5312026-09-14T23:57:03+00:00 – 2026-09-21T23:57:03+00:00
2026-09-2070.6252026-09-13T23:57:03+00:00 – 2026-09-20T23:57:03+00:00
2026-09-1969.0262026-09-12T23:57:03+00:00 – 2026-09-19T23:57:03+00:00
2026-09-1868.8272026-09-11T23:57:02+00:00 – 2026-09-18T23:57:02+00:00
2026-09-1768.6272026-09-10T23:57:03+00:00 – 2026-09-17T23:57:03+00:00
2026-09-1672.4292026-09-09T23:57:03+00:00 – 2026-09-16T23:57:03+00:00
2026-09-1567.1232026-09-08T23:57:03+00:00 – 2026-09-15T23:57:03+00:00
2026-09-1466.0252026-09-07T23:57:03+00:00 – 2026-09-14T23:57:03+00:00
2026-09-1372.5232026-09-06T23:57:03+00:00 – 2026-09-13T23:57:03+00:00
2026-09-1274.4222026-09-05T23:57:03+00:00 – 2026-09-12T23:57:03+00:00
2026-09-1171.0202026-09-04T23:00:04+00:00 – 2026-09-11T23:00:04+00:00
2026-09-1067.0202026-09-03T23:00:05+00:00 – 2026-09-10T23:00:05+00:00
2026-09-0962.2182026-09-02T23:00:04+00:00 – 2026-09-09T23:00:04+00:00
2026-09-0863.8222026-09-01T23:00:03+00:00 – 2026-09-08T23:00:03+00:00
2026-09-0764.2192026-08-31T23:00:03+00:00 – 2026-09-07T23:00:03+00:00
2026-09-0657.0192026-08-30T23:00:02+00:00 – 2026-09-06T23:00:02+00:00
2026-09-0550.6212026-08-29T23:00:03+00:00 – 2026-09-05T23:00:03+00:00

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.

RedditLatest scored opinion 2026-10-03 20:37 UTC54.616 opinionsvs 7d ago +10.8Hacker NewsLatest scored opinion 2026-09-30 22:39 UTC—3 opinionsInsufficient sampleZhihuLatest scored opinion 2026-10-02 13:33 UTC—4 opinionsInsufficient sampleRedNoteNo scored opinion timestamp—0 opinionsInsufficient sample

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.

Platform
Sentiment

4 selected excerpts

Community reports about limits cannot establish official allowances.

PositiveCoding

“Luna is worth testing on a small coding task with clear tests.”

Reddit · r/ChatGPT ↗
PositiveCoding

“GPT Plus has an excellent, low-cost programming model (GPT Luna)”

Reddit · r/DeepSeek ↗
PositiveCoding

“I still prefer 5.6 Luna xhigh and max for implementation and debug work”

Reddit · r/codex ↗

Explore long-term changes & analysis

Model lifecycle

GPT-5.6 Luna

Released 2026-07-10 · Back to GPT

Exact-version signals observed 2026-09-23–2026-10-03 · n=74

Data window: 2026-09-06 00:00:00 to 2026-10-04 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 2026-10-03

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
58.5
n=60
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.

14-day rolling experience4050602026-09-16–2026-09-30 · 54.8 · n=492026-09-17–2026-10-01 · 57.5 · n=532026-09-18–2026-10-02 · 57.7 · n=562026-09-19–2026-10-03 · 58.4 · n=582026-09-20–2026-10-04 · 58.5 · n=6008-1308-2208-3109-0909-1809-2710-04

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 → 9 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 → 0 Category change– Weight share– Experience contribution– Discussion-mix contribution–
Reasoning Baseline → currentnot enough datan=0 → 12 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 → 6 Category change– Weight share– Experience contribution– Discussion-mix contribution–
General text Baseline → currentnot enough datan=0 → 34 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.

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