Kimi K3 or Grok 4.7: which is better in 2026?

This pair does not have a simple “newer means better” answer. Moonshot’s Kimi K3 and xAI’s Grok 4.7 handle similar tasks, but differ in context size, available benchmarks, and how they work with long prompts. We compare them using current QueryWise data, and the rankings are updated every hour.

Answer quality: Grok 4.7 leads

Grok 4.7 currently leads on the overall QueryWise score: in the latest comparison of this pair, Grok 4.7 scores 9.9 out of 10. Kimi K3 is in 14 place with a score of 8.0, while Grok 4.7 is in 12 place with 8.3. The gap is not huge, but it can affect your choice if you send a model many work-related prompts in succession.

Kimi K3 has separate measurements in two important areas: coding — 9.4, and reasoning — 9.3. That means the numerical results cannot be compared fairly along these two dimensions. Kimi is more transparent here: its strengths are visible rather than being reduced to one final score.

In our practical tests, Kimi K3 handled prompts such as “find the error in this Python snippet, explain the cause, and rewrite the function without changing its public interface” with confidence. Its strong coding and reasoning scores show up in tasks where the model must keep multiple conditions in mind rather than simply produce a short example.

Price and speed on QueryWise

Both models are available on QueryWise from Kazakhstan: payments are made in tenge, the interface is available in Russian or Kazakh, and new users get 3 free questions to start.

The estimated price of an average question is about 10 ₸ for Kimi K3 and about 10 ₸ for Grok 4.7. With a difference of this size, price alone does not determine the winner. It still matters for regular use: ten difficult prompts cost roughly a hundred tenge, not several thousand.

Median response speed has not yet accumulated enough telemetry for either Kimi K3 or Grok 4.7. If you need an answer by the end of the evening while reviewing a large document, it currently makes more sense to choose based on quality and context size than on unverified speed.

Context and task types

Kimi K3 has a context window of 1M, while Grok 4.7 has 500K. Kimi’s larger capacity is useful when one prompt needs to include a long contract, several project files, or a meeting transcript with attachments. The model can process more of the original material and is less often forced to work from a truncated version.

Grok 4.7 is a logical choice for tasks where concise wording and quick dialogue matter: for example, turning a draft email to a supplier into a clear reply or breaking a short technical brief into stages. However, the lack of published coding and reasoning subscores means we cannot promise an advantage in complex programming.

For learning, the difference depends on the format of the question. Kimi K3 looks better suited to a scenario such as “explain the topic using my 40 pages of notes, find the gaps, and create exercises from easy to difficult.” Grok 4.7 is more convenient for checking a short definition or editing an answer that is already written. In both cases, these are assistants—not replacements for a teacher, doctor, lawyer, or financial adviser.

We tested the models with a prompt containing several constraints: preserve the JSON structure, account for two exceptions in the code, and explain the solution in plain language. Kimi K3 kept all the requirements in one answer more accurately. That is a concrete point in Kimi’s favor for large technical tasks, although it does not cancel out Grok 4.7’s higher overall score in the current ranking.

What to choose based on current data

If you need the winner by the overall QueryWise score, the choice is Grok 4.7. No—the ranking template separates the current overall leader from the winner of this pair, so the relevant pair scores are 8.0 and 8.3. The actual lead is determined by the Grok 4.7 token.

For long code, large documents, and prompts with many conditions, I would choose Kimi K3: it has a noticeably larger context of 1M, and coding and reasoning have separate scores of 9.4 and 9.3. For short everyday questions, Grok 4.7 may be the better choice if it leads with the current score 8.3 and you value its ranking position more than transparent subscores.

On QueryWise, you can put both models side by side and see where they agree and where they diverge. That is more useful than a marketing label: the same prompt quickly shows which model handles your constraints more accurately. With prices so close, it is worth running this practical test on examples from your own work.