Kimi K3.1 Pro vs Opus 5.5: the real cost per task, in dollars

Kimi K3.1 Pro vs Opus 5.5: Kimi charges exactly half per token ($2 in and $10 out per million, against Opus's $4 and $20). But per finished task the story changes: according to Artificial Analysis, a task costs $5.98 with Opus 5.5, $2.11 with Kimi, and only $0.72 with GPT-6.1 Sol. Here is the full math and how to measure it with your own tasks.

What changed on October 23 with Kimi K3.1 Pro

Almost everyone covered it as "a Chinese AI that nearly ties Opus." That's half the headline. Moonshot launched Kimi K3.1 Pro on October 23, 2026, with a one-million-token context window, and cut the price from K3: from $3 in and $15 out to $2 and $10 per million tokens.

Moonshot also promises to publish the weights before November 4, but today you can only use it through its API, its app, or Kimi Code.

How it works inside: experts and reasoning effort

It's a mixture-of-experts model: 2.8 trillion parameters, of which only about 104 billion are active per token (it picks 16 experts out of 896). That's why it runs without costing what it looks like it should.

The key piece is in the API: the reasoning effort parameter, with three values: low, high, and max. The default is max, and Moonshot reports all its results with maximum reasoning. Reasoning a lot means writing a lot, and every word it writes is billed as output. That idea explains the whole math.

How to test Kimi K3.1 Pro step by step

1. Create an account on Kimi's developer platform and generate an API key.
2. The API is OpenAI-format compatible: change the base URL, your key, and the model name (kimi-k3.1-pro).
3. On your first test, set reasoning effort to high, not max.
4. Send real tasks, not demo tasks, and read the usage field in each response: it shows how many tokens it wrote.

Where you get stuck the first time: sampling parameters are fixed (adjusting temperature does nothing), the Highspeed version (2 to 3 times faster) requires a paid plan, in Kimi Code you pick the model with the slash model command, and in Kimi Enterprise your admin has to turn it on because it ships switched off.

The math: Kimi K3.1 Pro vs Opus 5.5 and GPT-6.1 Sol

Artificial Analysis, an independent evaluator, runs the same task index on every model and measures what each task costs:

| Model | Cost per task | Quality (index) | Per 1,000 tasks | | --- | --- | --- | --- | | Claude Opus 5.5 | $5.98 | 58 | $5,980 | | Kimi K3.1 Pro | $2.11 | 55 | $2,110 | | GPT-6.1 Sol | $0.72 | 52 | $720 |

Kimi costs $3.87 less than Opus per task (65% less), but almost three times more than Sol. The reason is tokens: on that index Kimi wrote 150 million output tokens, against 67 million for Sol.

Three business cases

A development agency with coding agents. A repository and a list of tickets; the agent works for hours in Kimi Code without you watching. Moonshot reports 65.7% on Terminal-Bench 4.0 against Opus's 66.4%. At $2.11 per task instead of $5.98, the agency spends a little over a third as much. This is my own analysis, not a published case.

A small accounting firm with PDFs. A quarter's invoices and bank statements in the one-million-token window, to reconcile and summarize per client. Moonshot says it scores 64.4 on OfficeQA Pro v2; that's their number. Fitting a million tokens doesn't mean it uses them all well: split the work by client.

An online store with customer support. A three-tier rule: GPT-6.1 Sol handles the repetitive stuff ($0.72 per task), what it doesn't solve goes to Kimi, and anything touching money or contracts goes to Opus. Every task is solved on the cheapest model that can, but it requires measuring.

Who Kimi K3.1 Pro is not for

• If you handle regulated data, or customer data that can't leave the country: Moonshot offers zero data retention to API customers, but the company is based in China and your legal team has to review it.
• If you need fast, live answers: Artificial Analysis measures it at 41 tokens per second, among the seven slowest of 192 models.
• If your work is high-volume and simple: there, Sol costs almost three times less.

The strongest objection and what they don't tell you

An index isn't your tasks, and lowering reasoning effort does cut tokens. But Moonshot reports with effort at max: if you lower it, you're no longer buying the model they measured. Settle it with 20 of your own tasks on all three models at two effort levels. If your tasks are short, Kimi can come out better than this math.

On "nearly ties Opus, and it's open": today there are no weights to download, just a promise for November 4 with no published license, and Artificial Analysis classifies it as proprietary for now. Most quality figures were measured by Moonshot; on the independent index Opus wins 58 to 55. The hallucination figure (8.3% against Opus's 15%) comes from an internal stress test, not your everyday error rate.

What breaks in practice

• Verbosity: it saves per token but burns more tokens.
• Speed: at 41 tokens per second, a long agent run feels slow; Highspeed costs double ($4 / $20 per the price list checked).
• Migration: K2 models stop being available to new accounts on October 31 and are retired at the end of December.
• Cybersecurity: Moonshot removed cybersecurity data from training, and on its own offensive-security test the model dropped from 90.5 to 81.

How to apply it in your business?

The five-step rule: 1) gather 20 real tasks from your business; 2) run them on Sol, Kimi, and Opus; 3) measure output tokens, not price per token; 4) divide the cost by the tasks that came out right, that's your cost per success; 5) send each type of task to the cheapest model that solves it. Don't switch everything to Kimi because of a headline: on November 4 the weights come out along with the first independent data, and that's the date to repeat your test.

For the short version, read the full breakdown of Kimi K3.1 Pro and its open weights.

Frequently asked questions

Is Kimi K3.1 Pro cheaper than Claude Opus 5.5?

Per token, yes: half the price. Per task on the Artificial Analysis index too: $2.11 versus $5.98.

Is it cheaper than GPT-6.1 Sol?

No: per task it costs almost three times more ($2.11 versus $0.72).

Is Kimi K3.1 Pro open-weights?

Not yet. Moonshot promises to publish the weights before November 4 and hasn't said what license they'll carry.

What is reasoning effort?

An API parameter with values low, high, and max (the default). More reasoning means more output tokens and more cost.

Conclusion

In Kimi K3.1 Pro vs Opus 5.5, the price per token is the one on the label and the cost per task is the one on the invoice. The real question is which of your tasks deserves the expensive model. Measure with your own tasks before deciding.