Kimi K3 pricing for email summarization

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=500,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0165 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 email summarization benchmarks. Hover for details.

Cheapest viable option: Gemini 3 Flash at $0.003000/call (82% less, 83/100 quality).

What drives email summarization cost

Individually cheap, collectively expensive. A single thread is small, but summarization runs across an inbox at volume, so per-call price multiplied by message count is the number that matters, not the cost of any one summary. This is the use case where a fast-tier model and batch processing usually beat a smarter model outright.

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 3,000/500 token split, output accounts for 45% of the $0.0165 per-call cost.

Kimi K3 quality benchmarks for email summarization

Benchmark data for email summarization 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