Moonshot (Kimi) · Flagship · 1M context window

Kimi K3 pricing for marketing copy

$0.0474 per call at 800 input / 3,000 output tokens.

Per call

$0.0474

10K calls/mo

$474

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 marketing copy spend. Prices verified daily against provider pricing pages.

Configure your usage

800
100100K
3,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$474
10,000 calls/month
Cost per call$0.0474
Daily cost$16
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=3000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0474 per call at standard rates
# Input:  $3.00/MTok
# Output: $15.00/MTok

What drives marketing copy cost

Marketing copy is generated in variants (the same brief producing many versions for testing), so cost scales with variant count rather than brief length. Requesting several variants in one call is markedly cheaper than several calls, because the brief and brand context are sent once instead of repeatedly.

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 800/3,000 token split, output accounts for 95% of the $0.0474 per-call cost.

Complete Kimi K3 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$3.00800
Output$15.003,000

Prompt caching: 90% off input tokens

Caching drops input cost from $3.00 to $0.30/MTok. For repeated system prompts, that saves $0.002160 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$0.0474$474$452.4$21.6
50,000 calls$0.0474$2,370$2,262$108
100,000 calls$0.0474$4,740$4,524$216
500,000 calls$0.0474$23,700$22,620$1,080
1,000,000 calls$0.0474$47,400$45,240$2,160

Kimi K3 quality benchmarks for marketing copy

Benchmark data for marketing copy 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 marketing copy

11 models score 80+ on marketing copy benchmarks, sorted by input rate. Cheapest: Gemini 3.6 Flash (75% less, 76/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Kimi
Gemini 3.6 FlashGemini$0.75$3.7576/100$0.011875% cheaper
Gemini 3.7 FlashGemini$0.75$3.7582/100$0.011875% cheaper
Gemini 3.8 FlashGemini$0.75$3.7583/100$0.011875% cheaper
Gemini 3.5 FlashGemini$1.50$9.0075/100$0.028241% cheaper
Gemini 3.1 ProGemini$2.00$12.0077/100$0.037621% cheaper
Grok 4.6Grok$2.00$6.0078/100$0.019659% cheaper
Grok 4.7Grok$2.00$6.0075/100$0.019659% cheaper
GPT 5.4GPT$2.50$15.0079/100$0.04701% cheaper
GPT 5.6 SolGPT$4.00$20.0076/100$0.063233% more
Claude Opus 4.8Claude$5.00$25.0081/100$0.079067% more
Claude Fable 5.1Claude$10.00$50.0078/100$0.1580233% 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 marketing copy per API call?

A typical marketing copy call using Kimi K3 costs about $0.0474 per call. This estimate uses 800 input tokens and 3,000 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 marketing copy?

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

What is the cheapest model for marketing copy with good quality?

The most affordable model for marketing copy above 80/100 quality is Gemini 3.6 Flash. It comes from Gemini at $0.75 per million input tokens. Output costs $3.75 per million tokens with a quality score of 76/100. Switching from Kimi K3 to Gemini 3.6 Flash saves about 75% per API call.

How can I reduce my Kimi K3 costs for marketing copy?

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 $0.0474 to about $0.004740 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 marketing copy 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 marketing copy, typical calls use 800 input and 3,000 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.