GLM 5.2 or Claude Opus 5.5 — which is better on QueryWise?

Quality: the difference is immediate

In the QueryWise ranking, GLM 5.2 currently holds 24th place with a score of 6.7 out of 10. Claude Opus 5.5 is 1st with 9.9 out of 10. Claude Opus 5.5 is currently ahead by score. The current QueryWise ranking leader is Claude Opus 5.5, with a score of 9.9.

The gap between the models cannot be explained by answer formatting alone. Claude Opus 5.5 ranks first in QueryWise’s overall assessment, while GLM 5.2 sits noticeably lower in the table. Still, GLM is far from a weak option: its separate coding and reasoning scores are 8.7 and 9.2. For tasks that require a usable code draft or a step-by-step analysis of conditions, those are serious results.

It would be misleading to call Claude the winner in every specific category. Its overall score does give it a clear and fairly convincing advantage.

Speed and price in tenge

According to our telemetry, GLM 5.2 responds with a median latency of 13 seconds. Measurement reliability is 100%. For users, that means a straightforward experience: send a question and get an answer without a long wait. The average question costs approximately 10 ₸.

There is not yet enough data to establish median speed and reliability for Claude Opus 5.5, so this page uses — and 18. An average question costs approximately 18 ₸. With the same number of requests, Claude will cost more than GLM if current prices remain unchanged.

The difference becomes especially noticeable with regular use. Ten average questions sent to GLM work out to about 10 ₸ per request at the current price, while the same volume for Claude comes to roughly 18 ₸ per request. The wording may sound dry, but by the end of the month it becomes a real expense. For a short everyday question, paying extra for Claude may not be worthwhile; for a difficult task, the price of a stronger model can be justified.

Context and task types

The two models have context windows of 1M and 1M. That is enough to upload a large contract, technical documentation, or several related files and then ask questions about the content without constantly splitting the material into small pieces.

GLM 5.2 is a logical choice when you need to analyze a long text quickly and affordably. For example, you can upload a rental agreement and ask it to find clauses about early termination, penalties, and the procedure for returning a deposit. The model can structure the material, but legal conclusions still need to be checked: it is an assistant, not a lawyer.

GLM 5.2 looks particularly interesting for coding, with a score of 8.7. A representative test prompt is: “Find the bug in this Python snippet, explain the cause, and suggest a fix without changing the public API.” In this format, the model should trace the issue from symptom to fix rather than simply rewrite the entire codebase. We tested it with real questions of this kind: it handles logic confidently and suggests a patch, but the result should still be tested before deployment.

Claude Opus 5.5 is the more sensible choice when nuance and a coherent final result matter—for example, turning a long customer conversation into a clear action plan while preserving constraints, deadlines, and disputed points. It leads in QueryWise’s overall assessment, making it the current favorite for complex prompts with multiple conditions. However, separate coding and reasoning scores have not yet been published, so we will not present an assumption as a measured fact.

On QueryWise, you can give both models the same question and see where they agree and where they diverge. That is more useful than a polished ranking: when checking facts, matching wording does not prove that something is true, while differences quickly highlight areas worth verifying.

Which option should you choose?

If you want the highest overall score, choose Claude Opus 5.5: it is currently ahead. For complex analysis, a large set of instructions, or text where tone and context matter, Claude Opus 5.5 gets our primary recommendation.

If price, quick responses, and coding are the priorities, GLM 5.2 is the more practical option. Its current price is approximately 10 ₸ per average question, its median response time is 13 seconds, and its reliability in our telemetry is 100%. It is a good fit for everyday iterations: fixing a function, explaining an error, condensing a document, or creating a plan.

Both models are available from Kazakhstan: you can pay in tenge, use the interface in Russian or Kazakh, and receive 3 free questions when you start. Try the same difficult prompt in both systems first. The final choice is clear once you match the model to the task: Claude Opus 5.5 for overall output quality, and GLM 5.2 for economical speed and strong measured coding performance.