Moonshot (Kimi) · Flagship · 1M context window

Kimi K3 pricing for json extraction

$0.0210 per call at 3,000 input / 800 output tokens.

Per call

$0.0210

10K calls/mo

$210

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 json extraction spend. Prices verified daily against provider pricing pages.

Configure your usage

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

Estimated cost

Monthly cost
$210
10,000 calls/month
Cost per call$0.021
Daily cost$7
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: ~$0.0210 per call at standard rates
# Input:  $3.00/MTok
# Output: $15.00/MTok

What drives json extraction cost

Structured JSON output is compact and predictable, so cost is set almost entirely by how much source text you send. The schema itself is identical on every call and belongs in the cached prefix. This is also a task where a smaller model often matches a larger one: the output space is constrained by the schema, which limits how wrong a cheaper model can go.

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 3,000/800 token split, output accounts for 57% of the $0.0210 per-call cost.

Complete Kimi K3 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$3.003,000
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 $0.008100 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$0.0210$210$129$81
50,000 calls$0.0210$1,050$645$405
100,000 calls$0.0210$2,100$1,290$810
500,000 calls$0.0210$10,500$6,450$4,050
1,000,000 calls$0.0210$21,000$12,900$8,100

Kimi K3 quality benchmarks for json extraction

Benchmark data for json extraction 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 json extraction

2 models score 80+ on json extraction benchmarks, sorted by input rate. Cheapest: Gemini 3 Flash (81% less, 86/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Kimi
Gemini 3 FlashGemini$0.50$3.0086/100$0.00390081% cheaper
Claude Haiku 4.5Claude$1.00$5.0088/100$0.00700067% cheaper

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 json extraction per API call?

A typical json extraction call using Kimi K3 costs about $0.0210 per call. This estimate uses 3,000 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 json extraction?

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

What is the cheapest model for json extraction with good quality?

The most affordable model for json extraction 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 86/100. Switching from Kimi K3 to Gemini 3 Flash saves about 81% per API call.

How can I reduce my Kimi K3 costs for json extraction?

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 $0.0210 to about $0.002100 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 json extraction 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 json extraction, typical calls use 3,000 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.