Moonshot (Kimi) · Flagship · 1M context window

Kimi K3 pricing for pdf summarization

$0.0675 per call at 15,000 input / 1,500 output tokens.

Per call

$0.0675

10K calls/mo

$675

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 pdf summarization spend. Prices verified daily against provider pricing pages.

Configure your usage

15,000
100100K
1,500
5050K
10,000
1001M

Estimated cost

Monthly cost
$675
10,000 calls/month
Cost per call$0.0675
Daily cost$23
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=1500,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0675 per call at standard rates
# Input:  $3.00/MTok
# Output: $15.00/MTok

What drives pdf summarization cost

PDFs are the worst case for input cost: extracted text carries page furniture, headers, and footnotes that inflate token counts well past what the content warrants. Cleaning the extraction before sending it often cuts more cost than changing models. Long PDFs also routinely cross long-context pricing thresholds, so chunking is both a quality and a cost decision.

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 15,000/1,500 token split, output accounts for 33% of the $0.0675 per-call cost.

Complete Kimi K3 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$3.0015,000
Output$15.001,500

Prompt caching: 90% off input tokens

Caching drops input cost from $3.00 to $0.30/MTok. For repeated system prompts, that saves $0.0405 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$0.0675$675$270$405
50,000 calls$0.0675$3,375$1,350$2,025
100,000 calls$0.0675$6,750$2,700$4,050
500,000 calls$0.0675$33,750$13,500$20,250
1,000,000 calls$0.0675$67,500$27,000$40,500

Kimi K3 quality benchmarks for pdf summarization

Benchmark data for pdf 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.

Alternative models for pdf summarization

10 models score 80+ on pdf summarization benchmarks, sorted by input rate. Cheapest: Gemini 3 Flash (82% less, 83/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Kimi
Gemini 3 FlashGemini$0.50$3.0083/100$0.012082% cheaper
Gemini 3.6 FlashGemini$0.75$3.7575/100$0.016975% cheaper
Gemini 3.7 FlashGemini$0.75$3.7579/100$0.016975% cheaper
Gemini 3.8 FlashGemini$0.75$3.7581/100$0.016975% cheaper
Claude Haiku 4.5Claude$1.00$5.0082/100$0.022567% cheaper
Gemini 3.5 FlashGemini$1.50$9.0076/100$0.036047% cheaper
Gemini 3.1 ProGemini$2.00$12.0080/100$0.048029% cheaper
Grok 4.7Grok$2.00$6.0075/100$0.039042% cheaper
Claude Fable 5Claude$10.00$50.0077/100$0.2250233% more
GPT 6 AstraGPT$10.00$50.0076/100$0.2250233% 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 pdf summarization per API call?

A typical pdf summarization call using Kimi K3 costs about $0.0675 per call. This estimate uses 15,000 input tokens and 1,500 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 pdf summarization?

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

What is the cheapest model for pdf summarization with good quality?

The most affordable model for pdf summarization above 80/100 quality is Gemini 3 Flash. It comes from Gemini at $0.50 per million input tokens. Output costs $3.00 per million tokens with a quality score of 83/100. Switching from Kimi K3 to Gemini 3 Flash saves about 82% per API call.

How can I reduce my Kimi K3 costs for pdf summarization?

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 $0.0675 to about $0.006750 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 pdf summarization 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 pdf summarization, typical calls use 15,000 input and 1,500 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.