GLM 5.1 or GPT-6 Astra — Which Is Better in QueryWise?

GPT-6 Astra leads on quality

In the current QueryWise ranking, GPT-6 Astra is 4th with a score of 9.3 out of 10. GLM 5.1 is 28th and scores 5.6 out of 10. By the current score, GPT-6 Astra is ahead. This is more than a formality: the difference becomes clear in tasks that require tracking constraints, checking conclusions, and preserving the details of a prompt.

For reference, Claude Opus 5.5 is nearby with a result of 9.9, while Muse Spark 1.3 has a score of 8.6. GPT-6 Astra is already holding a place near the top of the table, while GLM 5.1 remains noticeably lower. QueryWise updates its rankings every hour, so this article keeps live values instead of freezing them on the publication date.

Coding

For coding, GLM 5.1 scores 7.5 out of 10, while GPT-6 Astra scores 9.5. Here, GPT-6 Astra has a convincing advantage. For a task like “find the bug in this Python function, explain why it fails, and rewrite the code with a test for empty input,” Astra is more likely to provide a complete solution rather than just point out where the error is.

GLM 5.1 is still a capable programming option. It makes sense when you need to draft an SQL query quickly, review a short JavaScript snippet, or get a second opinion on code that already works. But for a project involving several connected files, GPT-6 Astra’s higher score matters more than saving money on a single request.

Reasoning and difficult questions

GLM 5.1 scores 8.9 out of 10 for reasoning. That is its strongest area within its own evaluation. You can use the model to review a contract in plain language, check a chain of calculations, or prepare a research plan when the question fits into one clear context.

We therefore do not make a direct numerical comparison on this metric. Astra is still ahead overall, while GLM 5.1 remains an appealing choice for anyone who wants an inexpensive additional answer.

Price in tenge and speed

One average question costs about 10 ₸ with GLM 5.1 and around 43 ₸ with GPT-6 Astra. Astra costs more, and the difference is especially noticeable when working daily with long texts or running many rounds of code revisions. After ten average requests, it becomes a real difference in spending rather than a minor line item.

GLM 5.1 is the more sensible choice for preliminary work: generating options, cleaning up text, drafting an email, or checking a simple formula. GPT-6 Astra justifies its price when a mistake would cost more than the request itself—for example, during a review of complex code, analysis of a large specification, or preparation of a structured report.

QueryWise has not yet collected enough telemetry to establish the median speed of either model. We will not present missing measurements as an advantage for either side.

Context and task types

GLM 5.1 works with a context of 205K tokens. That is enough to spend an evening reviewing a 200-page contract section by section, highlighting disputed clauses, and asking several follow-up questions if the text is well prepared.

GPT-6 Astra has a context of 1.1M tokens. That is a different scale: the model is more convenient for a large repository, extensive technical documentation, or an email archive where important conditions are scattered far apart. A large context does not guarantee a flawless answer, but it reduces the need to split material across many separate chats.

We tested both models with real questions. Asked to “compare two office rental options in Almaty, calculate the monthly cost including utilities, and identify which data is missing,” GLM 5.1 organized the calculations well and listed gaps in the source data. Astra provided a more careful comparison structure and more clearly separated facts from the prompt from assumptions. Neither model should replace a lawyer or financial adviser.

In QueryWise, you can send the same question to both models and see where they agree and where they differ. This is especially useful for preliminary analysis and code checks: GLM 5.1’s inexpensive answer helps you find a direction quickly, while GPT-6 Astra serves as the stronger second check.

Verdict by use case

If you want the best result overall, the winner is GPT-6 Astra: the current score is 9.3 versus 5.6 for its competitor, and Astra also leads in coding. Choose GPT-6 Astra for large documents, complex coding, and tasks where mistakes are costly.

If cost is the priority, GLM 5.1 is the practical winner for frequent short requests: 10 ₸ versus 43 ₸ per average question. Its strong reasoning and 205K-token context make it a good budget assistant, but not the ranking leader.

Both models are available in QueryWise from Kazakhstan: payments are processed in tenge, the interface is available in Russian and Kazakh, and new users get three free questions to start. You can try them without a subscription. Start with GLM 5.1 for study and everyday writing, and switch to GPT-6 Astra for serious coding and long-form material.