Foundation Model · Amazon BedrockGeneral TierTextMulti-Tier Pricing
Amazon Bedrock token pricing and cost optimization reference for Kimi K3.Rates normalized to USD per 1 Million Tokens ($/1M) with prompt caching and batch API discounts across 36 AWS regions.
ProviderMoonshot AI
Maker HQBeijing, China
Class / TierGeneral
ModalityText
Prompt CachingSave 95%
Batch APISave 45%
AWS Regions36 Global
Bedrock Model ID
moonshot-ai.kimi-k3-v1:0Input / Prompt
$3.00/ 1M tokens
$0.0030 per 1K tokens
Output / Completion
$15.00/ 1M tokens
$0.0150 per 1K tokens
Prompt Cache Read
$0.15/ 1M tokens
Save 95% vs prompt
Batch Inference
$1.65/ 1M in
Save 45% via Batch API
Price Ratio
1 : 5.0
Prompt to completion factor
Alternatives to Kimi K3
| Option | Price vs Kimi K3 | Why look at it |
|---|---|---|
| Kimi K2.5Compare → | input-80%-$2.40/1M output-80%-$12.00/1M Standard tier, per 1M tokens | Next step down in price from Moonshot AI |
| Kimi K2 ThinkingCompare → | input-80%-$2.40/1M output-83%-$12.50/1M Standard tier, per 1M tokens | Same General line, different version |
Kimi K3 Spend Estimator
Model inference spend by prompt volume, cache hit rate, and batch processing.
M tokens
M tokens
30%
Estimated Monthly Spend
$0.00
Fresh Prompts:$0.00
Cached Prompts:$0.00
Completions:$0.00
Active: Input: $3.00/1M · Output: $15.00/1M
Key Cost Levers & Architecture
Practical mechanisms to reduce inference costs with Kimi K3 on AWSPrompt CachingSave ~95%
Caches repetitive system instructions, schemas, and document prefixes in memory with 5-minute and extended 1-hour TTL tiers.
- Read Rate: $0.15 / 1M tokens
- Write Rate (5m TTL): $1.88 / 1M tokens
- Ideal for: Multi-turn conversations, RAG document queries, structured schemas
Batch InferenceSave 45%
Asynchronous bulk processing submitted via Amazon S3 with a standard 24-hour turnaround SLA.
- Batch Input: $1.65 / 1M tokens
- Batch Output: $8.25 / 1M tokens
- Ideal for: Offline classification, synthetic data generation, benchmark evals
Cross-Region & Tiers36 Regions
AWS Bedrock supports standard on-demand inference, priority reserved throughput, and cross-region routing.
- Standard: Lowest latency, pay-per-token with zero commitments
- Cross-Region Routing: Automatically burst traffic to available regional capacity
- GovCloud: Dedicated isolated compliance partitions with +20% uplift
Regional Pricing Matrix
Live rates across all 36 available AWS cloud regionsBaseline: $3.00/1M inGovCloud: $3.60/1M in36 Global Regions
| AWS Region | Prompt Input $/1M | Completion Output $/1M | Cache Read $/1M | Batch Input $/1M | Pricing Tier |
|---|---|---|---|---|---|
| us-east-1 US East (N. Virginia) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| us-west-2 US West (Oregon) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-central-1 EU (Frankfurt) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-west-1 EU (Ireland) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-northeast-1 Asia Pacific (Tokyo) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| us-gov-west-1 AWS GovCloud (US-West) | $3.60 | $18.00 | $0.36 | $1.98 | GovCloud (+20%) |
| af-south-1 Africa (Cape Town) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-east-1 Asia Pacific (Hong Kong) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-south-2 Asia Pacific (Hyderabad) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-3 Asia Pacific (Jakarta) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-5 Asia Pacific (Malaysia) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-4 Asia Pacific (Melbourne) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-south-1 Asia Pacific (Mumbai) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-6 Asia Pacific (New Zealand) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-northeast-3 Asia Pacific (Osaka) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-northeast-2 Asia Pacific (Seoul) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-1 Asia Pacific (Singapore) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-2 Asia Pacific (Sydney) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-east-2 Asia Pacific (Taipei) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ap-southeast-7 Asia Pacific (Thailand) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| us-gov-east-1 AWS GovCloud (US-East) | $3.60 | $18.00 | $0.36 | $1.98 | GovCloud (+20%) |
| ca-central-1 Canada (Central) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| ca-west-1 Canada West (Calgary) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-west-2 EU (London) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-south-1 EU (Milan) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-west-3 EU (Paris) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-north-1 EU (Stockholm) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-south-2 Europe (Spain) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| eu-central-2 Europe (Zurich) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| il-central-1 Israel (Tel Aviv) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| mx-central-1 Mexico (Central) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| me-south-1 Middle East (Bahrain) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| me-central-1 Middle East (UAE) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| sa-east-1 South America (Sao Paulo) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| us-east-2 US East (Ohio) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
| us-west-1 US West (N. California) | $3.00 | $15.00 | $0.30 | $1.65 | Baseline |
No AWS regions found matching your filter.
Developer Quickstart
Invoke Kimi K3 via Amazon Bedrock Converse APIPython (boto3) · Amazon Bedrock Runtime
import boto3
# Amazon Bedrock Converse API invocation
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="moonshot-ai.kimi-k3-v1:0",
messages=[
{
"role": "user",
"content": [{"text": "Summarize key features and cost levers of Kimi K3."}]
}
],
inferenceConfig={
"maxTokens": 1024,
"temperature": 0.7
}
)
output_text = response["output"]["message"]["content"][0]["text"]
usage = response["usage"]
print(f"Response: {output_text}")
print(f"Usage: {usage['inputTokens']} in, {usage['outputTokens']} out")