GPT-5.4 mini vs Muse Spark 1.3 — which is better?

Quality: the difference is obvious right away

In the QueryWise ranking, GPT-5.4 mini is in 31 place with a score of 5.4 out of 10. Muse Spark 1.3 ranks 9 and scores 8.6 out of 10. Muse Spark 1.3 is currently ahead by score.

For context, the current top four in the QueryWise ranking are Claude Opus 5.5, GPT-6 Astra, Muse Spark 1.3, and Grok 4.7. GPT-5.4 mini is not on that list. That does not make OpenAI’s model weak, but it does show the scale of the gap: Muse Spark 1.3 is already close to the leaders, while GPT-5.4 mini is noticeably farther away.

A task-by-task breakdown adds some nuance. GPT-5.4 mini has a reasoning score of 8.6, while Muse Spark 1.3 currently has no separate value for this category. In coding, however, Muse Spark 1.3 scores 9.4, compared with 7.5 for GPT-5.4 mini. Meta’s advantage is convincing here.

Our practical test question was specific: “Find the bug in a Python function that incorrectly merges records by ID, explain the cause, and rewrite the code so that missing keys are handled explicitly.” GPT-5.4 mini usually breaks the problem down well and suggests a working fix. Muse Spark 1.3 is more confident specifically in coding: it reaches a corrected snippet faster and holds on to the task constraints better. That said, GPT-5.4 mini may offer a more careful explanation of the underlying logic.

Speed and price in tenge

There is not yet enough data in QueryWise telemetry to compare the models’ median response speeds. So claiming that one is consistently faster would be speculation. For users in Kazakhstan, the choice is straightforward for now: focus on the quality of the specific answer rather than an unverified difference in seconds.

The average question costs about 10 ₸ for GPT-5.4 mini and about 10 ₸ for Muse Spark 1.3. At this spending level, the price difference does not determine the choice. If you need to review several code snippets or draft an email in one evening, neither model turns the task into an expensive experiment.

We also do not yet have enough reliability data for GPT-5.4 mini or Muse Spark 1.3 in our telemetry. Treat this metric realistically: a model can handle one prompt perfectly and get the next one wrong, especially when the question involves facts, links, or ambiguous conditions.

Context and question types

GPT-5.4 mini works with a context of 400K, while Muse Spark 1.3 supports 1M. Muse Spark 1.3’s larger context is useful when you need to upload a long specification, several project files, or a large contract and then ask questions about the entire material. In a normal conversation, the difference will not be noticeable.

GPT-5.4 mini is the more logical choice when you need to check conditions in sequence—for example, compare two versions of a technical brief, find contradictions in the requirements, and prepare a list of questions for the client. Its reasoning score is 8.6, so the model performs well in structured analysis.

Muse Spark 1.3 is preferable when you need to process a codebase quickly, find a recurring error pattern, or suggest several optimization options. Its coding score is 9.4, which is stronger in the QueryWise ranking than GPT-5.4 mini’s 7.5 result by 9.4-level ranking. For a programming exercise, Muse Spark 1.3 will give the more practical first answer, while GPT-5.4 mini may do a better job explaining why the solution works.

There is also a practical everyday scenario. Suppose you upload a long instruction manual in Russian and Kazakh and ask it to find the product-return rules. Thanks to its 1M context, Muse Spark 1.3 looks better suited to handling the full document. GPT-5.4 mini is a good fit if you have already selected the relevant pages and want a clear summary.

Which model should you choose in QueryWise?

For coding, the winner is Muse Spark 1.3: its 9.4 score is notably higher than GPT-5.4 mini’s 7.5. Muse Spark 1.3 also has the advantage for long documents, with 1M context versus 400K. If you need a careful review of conditions, solid reasoning, and a step-by-step explanation, GPT-5.4 mini remains a strong option with a reasoning score of 8.6.

The overall ranking gives a clearer answer: Muse Spark 1.3 is currently ahead by score. With estimated prices of about 10 ₸ and 10 ₸ per average question, Muse Spark 1.3 offers better overall value across the measured characteristics if it is the current leader. If the ranking has changed and GPT-5.4 mini is now ahead, its advantage should be viewed as the result of fresh QueryWise measurements, not as a universal rule for every prompt.

In QueryWise, you can run both models side by side and see where they agree and where they differ. The service is available from Kazakhstan, payments are processed in tenge, the interface supports Russian and Kazakh, and new users get three free questions. It is a good way to test the models on your own document or code snippet. You should still verify the answers: QueryWise is an assistant, not a substitute for medical, legal, or financial advice.