GLM 4.7: what 43 developers actually say.

43 Hacker News opinions from 38 developers, Nov 2025 – Nov 2026. 39 come from people who say they use it. Here is what they praise, what they complain about, and who switched.

43 opinions38 developersNov 2025 – Nov 2026Methodology
Approval
56%
±12.5 at 90% confidence
Last 90 days
–
No recent data
Rank
#38
of 45 models · CI-adjusted
Opinions
43
39 first-hand
Developers
38
1.1 opinions each
The short version

The case for GLM 4.7, in one paragraph.

GLM 4.7 earns 56% approval across 43 opinions. Developers are divided on it.

Pick it if you

  • Want a cheap coding plan with generous usage limits
  • Need a pair programmer for routine debugging and small scripts
  • Are cutting costs on a multi-agent Claude Code setup

Look elsewhere if you

  • Work on large C++ or Rust changes where intent must hold
  • Need output you can trust without extra fixing
  • Expect problem solving close to Sonnet or Opus

Where it wins and loses.

Mentions across 43 opinions. Bars are counts, not votes; a tool can be both praised and criticized on the same topic.

TopicComplaints ← → PraiseMentions
Cost & pricing 10 mentions
19
Code quality 17 mentions
107
PraiseComplaint
2 topics shown · sorted by net sentiment · source: 43 opinions
View data table
TopicPraiseComplaintsMentions
Cost & pricing9110
Code quality71017

How opinion has moved.

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

62% Jan 202633% Jun 2026 low33% Jun 2026– last 90 days
0255075100APPROVAL56% all-time62%33%Jan '26Feb '26Mar '26Jun '26
Monthly approval, 0–100. Bars show opinion volume. Months with fewer than 3 opinions are left out.
View data table
MonthApprovalOpinions
Jan 202662%24
Feb 202656%8
Mar 202638%4
Jun 202633%3

What developers say.

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

Praise

4 selected
Speed

GLM 4.7 on Cerebras used to be amazing and wants much faster inference.

HN comment · Aug 14, 2026Read on HN ↗
Code quality

GLM 4.7 was good enough to help with a lot of work when used as a pair programmer.

HN comment · Jun 22, 2026Read on HN ↗
Speed

GLM 4.7 on Cerebras is their current pick: the smallest, fastest, cheapest model that gets the job done.

HN comment · Feb 12, 2026Read on HN ↗

GLM 4.7 has been performing very well so far.

HN comment · Feb 4, 2026Read on HN ↗

Complaints

4 selected
Code quality

GLM 4.7 Flash was far behind frontier models at launch, based on paid use and running it locally.

HN comment · Jun 25, 2026Read on HN ↗
Code quality

GLM 4.7 was extremely bad for agents writing simple 200-1000 line scripts.

HN comment · Jun 8, 2026Read on HN ↗
Code quality

The GLM 4.7 model they used on Cerebras is outdated.

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

GLM 4.7 clearly trails Sonnet and Opus in problem-solving ability.

HN comment · Apr 4, 2026Read on HN ↗

Questions developers ask.

Is GLM 4.7 worth it?
For cost-sensitive work, the data is favorable. Pricing is the strongest aspect at 9 positive and 1 negative comment. Code quality is the weakest at 7 positive and 10 negative, and reliability has 3 complaints and no praise.
Is GLM 4.7 better than Claude Opus?
Several users rank it below Sonnet and Opus. One describes it as less clever than Opus 4.5 while often getting the job done. One person preferred it over Claude Code.
Is GLM 4.7 good for coding?
The results split. Users report good results on debugging complex Neovim configs and on small pair-programming tasks. Others report failures on agent-written scripts of 200 to 1000 lines and uncertain quality on a C++ to Rust port.

The data behind this page.

Developers give GLM 4.7 a 56% approval score across 43 opinions from 38 people, and 39 of those opinions come from firsthand use. Cost is the clear strength: 9 of 10 pricing comments are positive, and users cite cheap coding plans with generous limits. Code quality is the weak spot at 7 positive and 10 negative comments, and reliability drew 3 complaints with none positive. Approval has drifted down from 62% in January 2026, when 24 opinions landed, to 38% in March and 33% in June. Those later months hold only 1 to 4 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 screened43 about GLM 4.739 first-hand

Read the full methodology →