GPT-5.4: what 114 developers actually say.

114 Hacker News opinions from 105 developers, Nov 2025 – Nov 2026. 101 come from people who say they use it. Here is what they praise, what they complain about, and who switched.

114 opinions105 developersNov 2025 – Nov 2026Methodology
Approval
72%
±6.9 at 90% confidence
Last 90 days
–
No recent data
Rank
#15
of 45 models · CI-adjusted
Opinions
114
101 first-hand
Developers
105
1.1 opinions each
The short version

The case for GPT-5.4, in one paragraph.

GPT-5.4 earns 72% approval across 114 opinions. Developers praise its code quality.

Pick it if you

  • Want strong code quality on large repositories
  • Need steady task adherence through long context compactions
  • Care about price at high usage volume

Look elsewhere if you

  • Need reliable orchestration of large multi-file workflows
  • Want security analysis on your own repositories
  • Expect accurate bug detection during code review

Where it wins and loses.

Mentions across 114 opinions. Bars are counts, not votes; a tool can be both praised and criticized on the same topic.

TopicComplaints ← → PraiseMentions
Code quality 51 mentions
1437
Cost & pricing 14 mentions
212
Reliability 17 mentions
710
PraiseComplaint
3 topics shown · sorted by net sentiment · source: 114 opinions
View data table
TopicPraiseComplaintsMentions
Code quality371451
Cost & pricing12214
Reliability10717

How opinion has moved.

Monthly approval, Mar 2026 – Sep 2026. Bars show opinion volume; low-volume months are still included but faded.

61% Mar 202644% May 2026 low100% Sep 2026– last 90 days
0255075100APPROVAL72% all-time61%44% low100%Mar '26Apr '26May '26Jun '26Jul '26Sep '26
Monthly approval, 0–100. Bars show opinion volume. Months with fewer than 3 opinions are left out.
View data table
MonthApprovalOpinions
Mar 202661%23
Apr 202675%61
May 202644%9
Jun 202691%11
Jul 202660%5
Sep 2026100%4

What developers say.

Summaries are paraphrased. Each links to the original Hacker News comment.

Praise

4 selected

GPT-5.4 hits a sweet spot at work: usually right, and easy to supervise and correct.

HN comment · Sep 10, 2026Read on HN ↗
Autonomy

Calls GPT-5.4 the best model they've tested for task adherence, even over multiple compactions.

HN comment · Sep 5, 2026Read on HN ↗
Reliability

GPT-5.4 is the only model that behaved well across context compactions on a large task.

HN comment · Aug 29, 2026Read on HN ↗
Customization

GPT-5.4 would prefer using LSP renaming tools as instructed.

HN comment · Jul 22, 2026Read on HN ↗

Complaints

4 selected
Reliability

GPT-5.4 started refusing to examine potential security problems in their repos.

HN comment · Jul 25, 2026Read on HN ↗

Feels GPT-5.4 has gotten worse than it used to be.

HN comment · Jul 17, 2026Read on HN ↗
Code quality

GPT 5.4 failed a complicated coding problem that Kimi 2.7 solved.

HN comment · Jun 17, 2026Read on HN ↗
Reliability

They were really frustrated with GPT-5.4 before their later Codex session went well.

HN comment · May 30, 2026Read on HN ↗

Questions developers ask.

Is GPT-5.4 worth it?
Most developers in this sample say yes, with 72% approval from 114 opinions. Cost is a commonly cited strength at 12 positive mentions against 2 negative. The main risk is instruction drift and uneven reliability over long sessions.
Is GPT-5.4 better than Claude Opus 4.6?
Sentiment leans toward GPT-5.4, with 10 people preferring it over Claude Opus 4.6 and 4 preferring Opus 4.6. That is opinion data only, with no benchmark results in the sample.
Is GPT-5.4 good for large codebases?
The data supports it, with 6 positive mentions for large codebases and none negative. Some users still report inconsistent orchestration on a 200-file QA workflow, so pair it with deterministic tooling for very large jobs.

The data behind this page.

GPT-5.4 holds 72% approval across 114 opinions from 105 authors, and code quality is the clearest strength at 37 positive mentions against 14 negative. Developers praise its task adherence, context compaction and price, with cost drawing 12 positive mentions and 2 negative, and 6 positive mentions on large codebases with no complaints. The trend is uneven: April 2026 carried most of the data at 61 opinions and 75% approval, while June through September total 21 opinions at 91% to 100% approval, so the recent rise rests on thin samples. Complaints focus on forgotten instructions, missed bugs in review, wasted effort checking diffs and weak orchestration of large workflows.

Every number comes from public Hacker News comments collected through the HN Search API. A language model tagged each comment for sentiment, first-hand use, topic and switches; a human spot-checks samples. No vendor can pay for placement.

20,064 comments screened114 about GPT-5.4101 first-hand

Read the full methodology →