Kimi K3 pricing for pr review

Quick start

Call Kimi K3 with the OpenAI Python SDK pointed at api.moonshot.cn:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.moonshot.cn/v1",
    api_key=os.environ["MOONSHOT_API_KEY"],
)
response = client.chat.completions.create(
    model="kimi-k3",
    max_tokens=3000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0690 per call at standard rates
# Input:  $3.00/MTok
# Output: $15.00/MTok

How Kimi K3 compares on cost

Per-call cost for all models scoring 50+ on pr review benchmarks. Hover for details.

Cheapest viable option: Claude Sonnet 5 at $0.0460/call (33% less, 96/100 quality).

What drives pr review cost

A pull request review carries the diff, the surrounding context, and often the PR description (heavy input, moderate output). Cost scales with PR size rather than with how much the model says, so the expensive reviews are the ones nobody wants to read anyway. Splitting large PRs is a cost control as much as an engineering practice.

For Kimi K3 specifically, that means output tokens cost 5.0x more than input, at $15.00 vs $3.00 per MTok. At this use case’s 8,000/3,000 token split, output accounts for 65% of the $0.0690 per-call cost.

Kimi K3 quality benchmarks for pr review

Benchmark data for pr review is pending for Kimi K3. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for Kimi K3. We recommend testing against your own evaluation criteria.

About Kimi K3

Prices from platform.kimi.ai (read 2026-10-11). Cache hit: $0.30/MTok input. Kimi K3 is a 2.8T-parameter open-weight MoE model. No batch discount published yet. Not yet benchmarked, so never recommended.

Other models from Moonshot (Kimi)

You can compare Kimi K3 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions