DeepSeek · Last 7 days
DeepSeek V4 Pro
0–100 · higher means more positive community experience, not benchmark performance.
Updated 2026-10-02 21:57 UTC · 2026-09-25 – 2026-10-02 UTCDiscussion overview
What the full sample discusses
All platforms · 18 eligible comments over 7 days, including usage-limit feedback; deduplicated by source and comment.
- General text · 11 comments: 5 positive / 6 negative / 0 mixed or neutral
- Reasoning · 2 comments: 2 positive / 0 negative / 0 mixed or neutral
- Coding · 1 comments: 0 positive / 1 negative / 0 mixed or neutral
- Image understanding · 1 comments: 0 positive / 0 negative / 1 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: −24.1 points vs 7 days ago. Discussion mix can affect scores; this does not establish a cause.
Source coverage and discussion concentration
Hacker News 2 · Reddit 14 · Zhihu 2
10 identifiable discussions cover 16/18 comments; the largest has 7. Remaining thread identities are unknown; this is not a count of independent users.
Selected individual opinions
One user claims V4 Pro has superior abilities compared to V4.1 Flash because it is a bigger model, attributing the advantage to model size. One user notes that DeepSeek V4 Pro is not a vision model, so a subagent (such as V4.1 Flash or Qwen) should be used for vision tasks.
About the sample and scores
As of 2026-10-02 21:57:03 UTC, DeepSeek V4 Pro in the DeepSeek family has 18 explicitly attributed community comments in the last 7 days; its community score is 43.5/100. Scoring method and sources
RECENT EXPERIENCE
How the Experience Index is changing
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.
No trend available
Hacker News · Not enough opinions · 2 scored comments · Read platform reviews →
ONE MODEL, DIFFERENT COMMUNITIES
Across the communities
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.
Explore long-term changes & analysis
Model lifecycle
DeepSeek V4 Pro
Released 2026-04-24 · Back to DeepSeek
Exact-version signals observed 2026-09-23–2026-10-01 · n=19
Data window: 2026-09-04 00:00:00 to 2026-10-02 00:00:00 UTC · Scoring method: experience_score_v3.
Lifecycle updated daily · latest complete UTC day 2026-10-01
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=19
- 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 → 2 | 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 → 1 | Category change– | Weight share– | Experience contribution– | Discussion-mix contribution– |
| Local deploy | Baseline → currentnot enough datan=0 → 1 | Category change– | Weight share– | Experience contribution– | Discussion-mix contribution– |
| Reasoning | Baseline → currentnot enough datan=0 → 3 | Category change– | Weight share– | Experience contribution– | Discussion-mix contribution– |
| Roleplay / creative | Baseline → currentnot enough datan=0 → 1 | 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 → 1 | Category change– | Weight share– | Experience contribution– | Discussion-mix contribution– |
| General text | Baseline → currentnot enough datan=0 → 10 | 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.
Community reviews
Selected comments from the last 7 days. The balance of excerpts does not represent the share of positive reviews.
0 selected excerpts
No selected comments for this filter in the last 7 days.