Kimi K3 in OpenCode: What One Finished Coding Task Actually Cost

Kimi K3 launched with impressive benchmark results—and a lot of debate about its price.

For developers using coding agents, however, price per million tokens is only part of the story.

A more useful question is:

How much does it cost to finish an actual coding task—with file reads, edits, tool calls, and passing tests?

We ran one controlled Kimi K3 coding task through OpenCode and recorded the result.

Disclosure: I work on Vancine, a third-party API aggregation platform. Vancine is not Moonshot AI and is not an official Kimi service. The cost below is measured Vancine usage for one specific run, not official Kimi pricing or a fixed-price promise.

The task

The agent received a small repository containing a faulty leap-year implementation.

It had to:

• inspect the source code and failing tests;


• identify the bug;


• edit the source file;


• leave the test file unchanged;


• run the actual test suite;


• finish with all tests passing.

The run used OpenCode v1.18.3 inside an isolated Docker Linux ARM64 environment.

The result

The 28,707 total tokens included:

• 3,746 input tokens;


• 1,019 output tokens;


• 902 reasoning tokens;


• 23,040 cached-read tokens.

The run completed without recorded HTTP 429 responses, HTTP 5xx responses, provider errors, or permission failures.

You can inspect the sanitized machine-readable evidence here:

You can also open the complete quick start here:

Kimi K3 API for coding agents

New Vancine accounts currently receive $1 in starting credit, with no credit card required.

Usage depends on the model, prompt size, context, tool loop, and number of requests. The starting credit does not guarantee that any particular coding task will complete within that amount.

The broader takeaway is simple:

For coding agents, measure the cost of reaching a tested solution—not just the price of generating a token.