DeepSeek V4 Pro on QueryWise: strong reasoning for a few tenge

DeepSeek V4 Pro’s main advantage is its long context

DeepSeek V4 Pro is a model from DeepSeek designed for tasks where a short prompt is not enough. Its main technical advantage is a 1M context window: you can upload a large contract, several code files, a client conversation, or a lengthy report and ask the model to work with the material as a whole. In practice, that is more convenient than repeating the previous background every time.

But a large context window does not turn a model into a universal genius. If a document is contradictory or contains a hidden error, DeepSeek V4 Pro may confidently build its answer on a false premise. The model is good at breaking tasks into steps, but the final result still needs to be checked.

In the QueryWise ranking, the model scored 7.8 out of 10 and sits in 14th place. Above it is currently MiniMax M3 with a score of 7.8, while Kimi 2.6 follows below with 7.8. For reference, the current top four are: Claude Fable 5, GPT-5.6 Sol, Kimi K3, Grok 4.5. This is not a leader’s position, but it is a strong result for an affordable assistant with a large context window.

My initial conclusion is simple: DeepSeek V4 Pro is most interesting for people who work with substantial source material, not just those looking for quick answers to everyday questions.

What the ranking and our measurements showed

DeepSeek V4 Pro’s overall QueryWise score is 7.8 out of 10. By category, the model received 8.1 for coding and 9.0 for reasoning. The second figure is particularly telling: the model can retain task constraints, identify relationships, and explain why it reached a particular conclusion.

Its coding performance is good, but not magical. DeepSeek V4 Pro can write a function, diagnose an error in Python or SQL, and suggest a fix plan. In a complex project, it sometimes chooses an elegant solution that ignores the existing architecture. Code like that should be run through tests before publication.

Our telemetry does not yet contain enough data for a fair conclusion about median response speed. Reliability is in the same position. We added the model on release day and will not present the first few observations as statistics. For a table-based comparison, it is more useful to look at 14th place and the 2.0-point gap to the leader than at unverified impressions.

QueryWise sends the same question to several leading neural networks, so you can compare DeepSeek with Claude Fable 5, GPT-5.6 Sol, Kimi K3, and Grok 4.5 in one interface. That is a major strength of the service: you can easily compare DeepSeek’s answer with alternatives without opening four tabs.

Questions it handles especially well

DeepSeek V4 Pro performs best when it needs to read conditions, identify the key points, and produce a clear step-by-step plan. For example: “Compare two home-internet plans in Almaty, calculate the monthly cost, and point out where the limitations are hidden.” If all the necessary data is in the prompt, the model neatly organizes prices, speeds, and extra charges.

A second strong category is working with business documents. The request “Turn this report into a brief for an executive, preserve the figures, and list the project risks separately” is well suited to its long context. It can keep a large amount of source text in view without reducing the answer to a random summary of the opening paragraphs.

A third example is programming: “Find the cause of the error in this Python snippet, explain it in simple terms, and suggest a fix without third-party libraries.” With a 8.1 coding score, the model looks convincing, especially for small scripts, SQL queries, and spreadsheet automation.

It is less reliable with questions requiring fresh data, local rules, or verified facts. For example, you should not rely on the answer to “Which bus is definitely running from Almaty airport to the city center today, and when is the next one?” without checking the current timetable. The model may sound confident even when no source has been provided. For medical, legal, and financial decisions, it is a drafting assistant—not a final adviser.

Where DeepSeek V4 Pro starts to struggle

The main drawback is its confident tone despite incomplete certainty. This is common among language models, but errors in long answers look especially plausible: correct reasoning, formulas, and polished subheadings appear alongside them. A user may miss one incorrect fact among a large amount of useful text.

The huge 1M window also requires discipline. If you upload everything indiscriminately—old document versions, duplicate tables, and outdated instructions—the model may not understand which file should take priority. Clearly specify dates, priorities, and the expected output format.

With a 9.0 reasoning score, DeepSeek V4 Pro is stronger than an average assistant on multistep tasks. That does not mean it is error-free in mathematics or logic. Ask it to show intermediate calculations, then verify them separately. Coding is similar: a 8.1 score is good, but it does not replace testing and code review.

There is also a market limitation. With an overall score of 7.8, the model trails the current leader, Claude Fable 5, which scored 9.8, as well as several strong alternatives nearby in the ranking. If you need the most stable answer for an important presentation, compare results from several models through QueryWise. DeepSeek V4 Pro is a capable working option, but it should not automatically become the final judge.

Price in tenge and final verdict

The average price per question on QueryWise is ≈10 ₸. For a short prompt, that seems reasonable—especially when compared not with the cost of a subscription, but with the value of the time spent reading a document or finding the cause of an error. The model is available to users in Kazakhstan, payment can be made in tenge, and the service offers three free questions at launch.

The QueryWise interface is available in Russian and Kazakh. DeepSeek V4 Pro itself performs best in Russian and English, but Kazakh prompts are worth trying too: results depend on the topic, wording, and volume of the source material. For important Kazakh-language text, I would ask the model to preserve terminology first, then have a person proofread the editing.

For its price, DeepSeek V4 Pro is particularly useful to programmers, analysts, students working through extensive notes, and office employees dealing with regulations. It is less convincing as a source of breaking news, exact schedules, or personalized recommendations. In those cases, comparing it with Claude Fable 5, GPT-5.6 Sol, Kimi K3, Grok 4.5 is more useful than relying on a single answer.

My verdict: this is a strong working model with excellent reasoning and an unusually large context reserve. 14th place shows that it is not yet the leader, but the ≈10 ₸ price makes experimentation nearly painless. Start with the three free questions, upload a real document, and compare the answer with other models—this will reveal its character faster than any marketing presentation.