GPT-OSS 120B or Kimi K3.1 Pro: which is better?

This is a comparison of two models built around different priorities. GPT-OSS 120B focuses on reasoning and affordability, while Kimi K3.1 Pro stands out with a larger context window and a stronger overall result. The gap between them in the QueryWise ranking is large enough that the conclusion cannot be hidden behind “it depends on the task.”

Quality: the difference is clear right away

GPT-OSS 120B currently ranks 37 in QueryWise, with a score of 3.7 out of 10. The model has one strength that is hard to overlook: its reasoning score is 9.9 out of 10. For tasks that involve unpacking a problem, spotting contradictions, or building a chain of conclusions, that is a convincing result.

Its coding performance is more modest: GPT-OSS 120B scores 5.0 out of 10. It can produce a working code fragment, but complex architecture and lengthy debugging usually call for additional review. This is not a failure, but it is a limitation that becomes visible next to the ranking leaders.

Kimi K3.1 Pro ranks 3 with a score of 9.5 out of 10. By the current score, Kimi K3.1 Pro is ahead. QueryWise does not yet publish separate coding and reasoning scores for Kimi, so assigning specific numbers would be misleading. The overall assessment is clear enough, though: Kimi is among the leaders, while GPT-OSS 120B is noticeably lower.

Above Kimi in the current table is Claude Opus 5.5, with a score of 9.9 out of 10. GPT-6 Astra and Gemini 4 Argon each score 9.3. GPT-OSS 120B is not part of this top group.

Price and speed: the same cost does not make models equivalent

An average question to GPT-OSS 120B costs about 10 ₸. QueryWise lists approximately 10 ₸ for an average question to Kimi K3.1 Pro as well. The difference is barely relevant to your budget: even over ten questions, it is not enough to justify choosing the weaker option.

There are not yet enough median speed measurements for either model. So we cannot promise that one consistently answers faster than the other. It is better to acknowledge that gap than to turn a single fast response into a claim about the model as a whole.

For users in Kazakhstan, the setup is equally straightforward: both models are available in QueryWise, payments are made in tenge, and the interface is available in Russian and Kazakh. New users can ask three free questions at the start. It is a convenient way to test the models on your own material without immediately buying a separate subscription.

Context and real-world tasks

GPT-OSS 120B has a context window of 131K tokens. That is enough to analyze several report chapters, rewrite a function, or find errors in a technical specification. The model is especially worth trying when the prompt is precise and the answer can be checked against the source data.

Kimi K3.1 Pro works with a context window of 1M tokens. That is a different level of capacity. If you need to load a large contract, an archive of correspondence, and a requirements table in one request, Kimi is more practical: you need to split the material into fewer parts and repeat less background information.

We tested the models with a concrete scenario: “Compare two versions of a supply contract, find the clauses on penalties, payment terms, and unilateral termination, then prepare a list of risks with references to the relevant sections.” GPT-OSS 120B built the response logic well, but its section references in the long document needed separate verification. Kimi K3.1 Pro retained more of the source material and produced a more coherent map of the differences. This is exactly the kind of case where context affects the practical result.

For another prompt, such as “Write a Python function that cleans Kazakh and Russian phone numbers, add tests, and explain edge cases,” GPT-OSS 120B may be a sensible choice thanks to its strong reasoning score, but the code still needs to be run. Prefer Kimi when the task is part of a larger project and you need to provide documentation, existing files, and a bug history along with the requirements.

There is also an educational scenario: walk through a probability problem, point out an error in the reasoning, and provide a similar example. Here, GPT-OSS 120B looks appealing with its reasoning result of 9.9. But for creating notes from a long course whose materials are collected in one large file, Kimi retains the context advantage.

Verdict by use case

If you want the best overall result, the winner is clear: by the current score, Kimi K3.1 Pro leads with. Choose Kimi K3.1 Pro for long documents, large datasets, and work where the model needs to remember many details from a single prompt.

GPT-OSS 120B makes more sense for focused reasoning tasks where price and the ability to quickly verify the answer matter. It is particularly appealing if you do not need a million-token context but want strong logical processing for around 10 ₸.

In QueryWise, you can submit both models side by side in one request and see where they agree and where they diverge. For contracts, code, and disputed conclusions, that is more useful than blindly trusting a single generation. Neither GPT-OSS 120B nor Kimi K3.1 Pro replaces medical, legal, or financial advice: facts and consequences should be checked separately.