ChatGPT 5.4 Review: Reliability, Reasoning, and Daily Work

Last updated: 2026-08-12 · This is a workflow review, not a frozen benchmark or price sheet. Availability follows ChatGPT.

Where 5.4 fits: a known baseline can beat novelty

After newer models appear, 5.4 can remain useful because teams know its output style, prompts are tuned, and failure modes are familiar. The right question is not “Is it newest?” but “Does it finish our work with acceptable rework?”

Workload	Supply	Pass condition	Main risk
Meeting notes	Transcript, owners, dates	Separates discussion from decisions	Invented owner
Research summary	Conflicting sources	Preserves attribution and disputes	Fake consensus
Code repair	Error, tests, interface limits	Minimal tested change	Unrelated rewrite
Long-form edit	Audience, fact list, old draft	Better structure, facts intact	Altered numbers or negation

Office work

Convert a meeting transcript into decisions, actions, owners, and dates. When no owner is named, a reliable model writes “to confirm” instead of assigning the loudest speaker.

Research

Ask who claims what, which evidence supports it, and why sources cannot be directly compared. Compressing opposing claims into “both have advantages” is over-synthesis, not insight.

Code

Require an explanation of the failing test and a list of intended files before a patch. Penalize unnecessary refactors. Production code passes only after local execution—not after a confident chat message.

Editing

After the rewrite, request a map from each original fact to its new location. This catches changed dates, quantities, actors, and negations.

Measure reliability

Run one prompt five times and record hard-constraint pass rate, severe factual errors, follow-up rounds, human correction minutes, and format stability. One spectacular output cannot compensate for one boundary-breaking run in an unattended workflow.

Common repairs:

• Repeat non-negotiable constraints at the start and end.
• State: “Missing information must be marked to confirm.”
• Require prerequisites and rollback for every plan step.
• Make test output—not prose—the code acceptance criterion.

Use only supplied material. Write “to confirm” for missing information.
Output: conclusion, evidence location, disagreement, risk, next action.
Finally audit every non-negotiable constraint: [list].

Keep 5.4 or migrate?

Keep it when current prompts pass reliably, the team knows its boundaries, newer models do not lower correction time, and consistency matters. Test migration when complex tasks repeatedly need rescue, a newer model lowers severe errors on your ten historical tasks, or 5.4 no longer offers required tools or capacity.

Do not replace every workflow at once. Parallel-run low-risk tasks for a week, then compare. For the next candidate, see the ChatGPT 5.5 review.

FAQ

Is an older model necessarily worse?

No. Task shape, mode, prompt, and tools matter. A larger version number cannot replace regression tests.

Where do I confirm the active model?

Use the selector at ChatGPT; API users should inspect OpenAI Platform model settings and request logs.

What about access in China?

Compare the official route with a domestic entry on sanitized tasks, but do not assume identical model names, tools, or privacy terms.