Kimi K2 pricing for chain of thought

Quick start

Call Kimi K2 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-k2",
    max_tokens=5000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0229 per call at standard rates
# Input:  $0.95/MTok
# Output: $4.00/MTok

How Kimi K2 compares on cost

Per-call cost for all models scoring 50+ on chain of thought benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.006600/call (71% less, 86/100 quality).

What drives chain of thought cost

Reasoning tasks invert the usual ratio: the model produces far more tokens than it consumes, because the intermediate steps are the work. Output pricing dominates completely, and models that reason at length cost more than their headline rate suggests. Comparing reasoning models on input price is actively misleading; compare them on output.

For Kimi K2 specifically, that means output tokens cost 4.2x more than input, at $4.00 vs $0.95 per MTok. At this use case’s 3,000/5,000 token split, output accounts for 88% of the $0.0229 per-call cost.

Kimi K2 quality benchmarks for chain of thought

Benchmark data for chain of thought is pending for Kimi K2. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for Kimi K2. We recommend testing against your own evaluation criteria.

About Kimi K2

Prices from platform.kimi.ai (K2.6, read 2026-10-11). Cache hit: $0.16/MTok input. Batch API at 60% of standard rate. Not yet benchmarked, so never recommended.

Other models from Moonshot (Kimi)

You can compare Kimi K2 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