Moonshot (Kimi) · Flagship · 1M context window

Kimi K3 pricing for faq bot

$0.0165 per call at 1,500 input / 800 output tokens.

Per call

$0.0165

10K calls/mo

$165

Cache savings

90% off input

Batch savings

0% off all

Calculate your Kimi K3 costs

Adjust token counts, volume, and discount toggles to model your faq bot spend. Prices verified daily against provider pricing pages.

Configure your usage

1,500
100100K
800
5050K
10,000
1001M

Estimated cost

Monthly cost
$165
10,000 calls/month
Cost per call$0.0165
Daily cost$6
Input rate$3.00/MTok
Output rate$15.00/MTok
Analyze your real spend

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=800,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0165 per call at standard rates
# Input:  $3.00/MTok
# Output: $15.00/MTok

What drives faq bot cost

The most bounded question-answering shape: a short question against a fixed knowledge base, with a short answer. Because the knowledge base never changes between calls, cache reads apply to nearly the entire input, and the effective cost per answer falls well below the list rate. A fast-tier model is usually sufficient when the answers are already written.

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 1,500/800 token split, output accounts for 73% of the $0.0165 per-call cost.

Complete Kimi K3 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$3.001,500
Output$15.00800

Prompt caching: 90% off input tokens

Caching drops input cost from $3.00 to $0.30/MTok. For repeated system prompts, that saves $0.004050 per call.

Batch API: 0% off all tokens

Submit requests asynchronously and receive 0% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.0165$165$124.5$40.5
50,000 calls$0.0165$825$622.5$202.5
100,000 calls$0.0165$1,650$1,245$405
500,000 calls$0.0165$8,250$6,225$2,025
1,000,000 calls$0.0165$16,500$12,450$4,050

Kimi K3 quality benchmarks for faq bot

Benchmark data for faq 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.

Alternative models for faq bot

12 models score 80+ on faq bot benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (92% less, 85/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Kimi
GPT 5.6 LunaGPT$0.20$1.2085/100$0.00126092% cheaper
Claude Haiku 4.5Claude$1.00$5.0086/100$0.00550067% cheaper
Gemini 3.5 FlashGemini$1.50$9.0084/100$0.00945043% cheaper
Claude Sonnet 5Claude$2.00$10.0089/100$0.011033% cheaper
GPT 5.6 TerraGPT$2.00$12.0092/100$0.012624% cheaper
Gemini 3.1 ProGemini$2.00$12.0087/100$0.012624% cheaper
GPT 5.4GPT$2.50$15.0091/100$0.01585% cheaper
Claude Sonnet 4.6Claude$3.00$15.0088/100$0.0165same cost
GPT 5.6 SolGPT$4.00$20.0091/100$0.022033% more
Claude Opus 4.8Claude$5.00$25.0085/100$0.027567% more
GPT 5.5GPT$5.00$30.0090/100$0.031591% more
Claude Fable 5Claude$10.00$50.0088/100$0.0550233% more

About Kimi K3

Provider

Moonshot (Kimi)

Tier

Flagship

Context

1M tokens

Released

Not published

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)

ModelTierInput $/MTokOutput $/MTokContext
Kimi K2Mid-tier$0.95$4.00256K

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

How much does Kimi K3 cost for faq bot per API call?

A typical faq bot call using Kimi K3 costs about $0.0165 per call. This estimate uses 1,500 input tokens and 800 output tokens at standard rates. Standard rates are $3.00 per million input tokens and $15.00 per million output tokens.

Is Kimi K3 the best model for faq bot?

Our benchmark data does not yet include a faq bot ranking for Kimi K3. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for faq bot with good quality?

The most affordable model for faq bot above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 85/100. Switching from Kimi K3 to GPT 5.6 Luna saves about 92% per API call.

How can I reduce my Kimi K3 costs for faq bot?

Three strategies lower Kimi K3 costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 0% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.0165 to about $0.001650 per call.

How does Kimi K3 pricing compare to other Moonshot (Kimi) models?

Moonshot (Kimi) has 1 other models alongside Kimi K3 today: Kimi K2 at $0.95/$4.00 per million tokens (mid-tier). The right choice depends on whether your faq bot workload prioritizes quality, cost, or speed.

What context window does Kimi K3 support?

Kimi K3 supports a context window of 1M tokens per API call. This sets the maximum combined length of your input prompt and generated response. For faq bot, typical calls use 1,500 input and 800 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.