Kimi K3 pricing for customer support bot

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=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0240 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 customer support bot benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001800/call (93% less, 85/100 quality).

What drives customer support bot cost

Support bots combine RAG's retrieved context with a chatbot's growing history, so they carry both cost curves at once. Volume is high and margins per conversation are thin, which makes the per-call rate matter more than in almost any other use case here. Caching the knowledge base and product context is the single highest-leverage change.

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 3,000/1,000 token split, output accounts for 63% of the $0.0240 per-call cost.

Kimi K3 quality benchmarks for customer support bot

Benchmark data for customer support bot 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