GPT-OSS 120B or Gemini 4 Argon: which is better?

This is not a close contest on quality

In the QueryWise ranking, GPT-OSS 120B scores 3.7 out of 10 and ranks 37th. Gemini 4 Argon scores 9.3 out of 10 and sits in 6th place. Gemini 4 Argon currently leads on score.

The gap becomes especially clear against the wider ranking. Gemini 4 Argon is positioned near GPT-6 Astra, which scores 9.3, while GPT-OSS 120B is noticeably below the leading group. Claude Opus 5.5 currently holds first place with a score of 9.9.

That does not make GPT-OSS 120B useless. It has a particularly strong reasoning score: 9.9. For tasks that require working through a condition step by step, finding a contradiction, or checking a line of reasoning, the model can be precise. But the overall QueryWise score measures more than one capability, and its coding result is weaker: 5.0.

So it would be misleading to call it the winner in every individual category. Still, the overall scores of 9.3 versus 3.7 already give a practical answer for most users.

The price is similar, but the value of each request is not

An average question costs approximately 10 ₸ with GPT-OSS 120B and about 10 ₸ with Gemini 4 Argon. The price difference is not enough to make the cheaper model an obvious choice: based on current data, both models are at roughly the same spending level.

For a short question, the difference is barely noticeable. Ten requests cost roughly ten average tariffs for each model, rather than making one option several times more expensive. The total changes with QueryWise’s live pricing, so use token counts as your guide instead of old screenshots or someone else’s review.

My practical takeaway is simple: at the same price, Gemini 4 Argon looks like the better deal for tasks where you need a correct answer on the first try. GPT-OSS 120B makes sense when its stronger reasoning matters more and you can verify the answer manually.

Context matters when there are lots of documents

GPT-OSS 120B has a context window of 131K, while Gemini 4 Argon offers considerably more: 1M. This is not just an abstract specification. If you need to review a 200-page contract, lengthy technical documentation, or several requirement files in one evening, Gemini 4 Argon’s extra capacity is more convenient.

GPT-OSS 120B performs best with a compact, clearly defined question. For example: “Find the error in this reasoning about probability and explain every incorrect step.” Its 9.9 reasoning score looks convincing here. The model can break the task down step by step instead of settling for a brief answer.

The picture is more cautious for coding. For a request such as “fix this Python function, preserve its behavior for an empty list, and write two tests,” GPT-OSS 120B scores 5.0. That is enough for simple edits, but you should run and verify the result.

There is also a third scenario: a large body of material in Russian and Kazakh. Uploading it to Gemini 4 Argon is more practical because of its 1M context window. For a single paragraph or task, that extra capacity matters less, and GPT-OSS 120B may be more comfortable when you need a detailed logical explanation.

What happens on QueryWise

Both models are available from Kazakhstan on QueryWise: payments are made in tenge, the interface is available in Russian and Kazakh, and new users receive three free questions at the start. You can send the same prompt to both models and see where their answers agree and where they differ.

We ran them through real questions. On tasks with lengthy instructions, GPT-OSS 120B carefully maintains the reasoning chain, but its practical answers sometimes need an extra clarification. Gemini 4 Argon is more convenient when one prompt contains a lot of source material and you want a consolidated result without manually splitting the text. This observation does not replace the live ranking, but it helps explain the difference between their scores.

An honest verdict

There is one winner on the current score: Gemini 4 Argon. For studying, reviewing large materials, and questions where overall answer quality matters, choose Gemini 4 Argon if 9.3 remains above 3.7. Its advantage is reinforced by a 1M context window, while the price is about 10 ₸ per average question.

GPT-OSS 120B gets my pick in a narrower scenario: you need to check complex reasoning in a small amount of text, and you can read the answer carefully and correct it if necessary. Its 9.9 score deserves attention, although its overall score of 3.7 leaves the model in 37th place.

There is no clear winner on speed yet: QueryWise’s median measurements do not include enough data for GPT-OSS 120B and Gemini 4 Argon. So speed claims should not drive the decision. With similar estimated prices and the current score gap, Gemini 4 Argon looks like the sensible default, while GPT-OSS 120B remains a specialized option for logic-heavy tasks.