GPT-5.3 Codex: what 54 developers actually say.

54 Hacker News opinions from 51 developers, Nov 2025 – Nov 2026. 51 come from people who say they use it. Here is what they praise, what they complain about, and who switched.

54 opinions51 developersNov 2025 – Nov 2026Methodology
Approval
74%
±9.8 at 90% confidence
Last 90 days
–
No recent data
Rank
#18
of 45 models · CI-adjusted
Opinions
54
51 first-hand
Developers
51
1.1 opinions each
The short version

The case for GPT-5.3 Codex, in one paragraph.

GPT-5.3 Codex earns 74% approval across 54 opinions. Developers praise its code quality.

Pick it if you

  • Work on backend and systems tasks
  • Need a low-cost daily driver for scripting and greenfield work
  • Care most about price for everyday coding

Look elsewhere if you

  • Work mainly in R
  • Need dependable long autonomous runs
  • Need strict test coverage and clean refactors

Where it wins and loses.

Mentions across 54 opinions. Bars are counts, not votes; a tool can be both praised and criticized on the same topic.

TopicComplaints ← → PraiseMentions
Code quality 23 mentions
716
Cost & pricing 10 mentions
19
PraiseComplaint
2 topics shown · sorted by net sentiment · source: 54 opinions
View data table
TopicPraiseComplaintsMentions
Code quality16723
Cost & pricing9110

How opinion has moved.

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

79% Feb 202657% Mar 2026 low80% Jun 2026– last 90 days
0255075100APPROVAL74% all-time79%57% low80%Feb '26Mar '26Apr '26Jun '26
Monthly approval, 0–100. Bars show opinion volume. Months with fewer than 3 opinions are left out.
View data table
MonthApprovalOpinions
Feb 202679%19
Mar 202657%15
Apr 202672%9
Jun 202680%5

What developers say.

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

Praise

4 selected
Code quality

Considers GPT-5.3 Codex the peak of coding models and misses it for writing good code without overstepping.

HN comment · Sep 2, 2026Read on HN ↗
Code quality

GPT-5.3-Codex was excellent for backend and systems tasks.

HN comment · Jul 10, 2026Read on HN ↗
Cost & pricing

GPT-5.3 Codex balances quality and cost well, cheap enough to use on almost everything.

HN comment · Jul 5, 2026Read on HN ↗
Cost & pricing

Calls GPT-5.3 Codex possibly OpenAI's best coding model, about 90% of GPT-5.5 at a fraction of the cost.

HN comment · Jun 30, 2026Read on HN ↗

Complaints

4 selected

Had poor results with GPT-5.3 Codex, so used GPT-5.2 for design and 5.3 Codex only for execution.

HN comment · Jun 20, 2026Read on HN ↗
Code quality

GPT-5.3-Codex falls short on R programming work.

HN comment · Apr 15, 2026Read on HN ↗
Reliability

Started quickly but got stuck in a five-hour loop that made no further progress on the clone task.

HN comment · Apr 2, 2026Read on HN ↗
Code quality

Describes Codex 5.3 injecting a CSS hack instead of properly refactoring the markup.

HN comment · Mar 12, 2026Read on HN ↗

Questions developers ask.

Is GPT-5.3 Codex worth it?
Most opinions are positive: approval is 74% across 54 opinions. Code quality and cost score well. Reliability is mixed at 3 positive and 4 negative comments.
Is GPT-5.3 Codex better than Claude Opus 4.6?
Five developers preferred GPT-5.3 Codex to Opus 4.6, and two preferred Opus 4.6. Cost is a common reason to pick Codex, though some said quality falls short on harder work.
Is GPT-5.3 Codex reliable?
Reliability comments lean negative at 3 positive and 4 negative. Reports describe a five-hour loop with no progress and tests that overstated coverage.

The data behind this page.

GPT-5.3 Codex has 74% approval across 54 opinions from 51 authors. Developers praise its code quality (16 positive, 7 negative) and cost (9 positive, 1 negative), and several prefer it to Claude Opus 4.6 or GPT-5.5. Reliability is the weak spot at 3 positive and 4 negative, with reports of long loops and weak tests. Approval was 57% in March 2026, then 72% to 100% in the April to September entries, which have only 2 to 9 opinions each.

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 screened54 about GPT-5.3 Codex51 first-hand

Read the full methodology →