# Kimi K3
##  Moonshot AI — Kimi K3
## Model Details
Kimi K3 is Moonshot AI's most capable open-weight model, combining native vision with a 1-million-token context window for long-running coding and knowledge workflows that sustain context across large repositories, documents, and images. For more information about model development and performance, see the [model/service card](https://huggingface.co/moonshotai/Kimi-K3).
+ **Model launch date:** 18th Sept 2026
+ **EOL no sooner than:** Not Applicable, at least 45 day EOL Notice will be provided
+ **Legacy period:** at least 45 days
+ **Model lifecycle policy:** [Bedrock Model Lifecycle](model-lifecycle.md)
+ **Model EOL date:** N/A
+ **End User License Agreements and Terms of Use:** [View](https://huggingface.co/moonshotai/Kimi-K3/blob/main/LICENSE)
+ **Model lifecycle:** Active
+ **Context window:** 1M tokens
| **Input Modalities** | **Output Modalities** | **[APIs supported](apis.html)** | **[Endpoints supported](endpoints.html)** |
| --- | --- | --- | --- |
|  Audio |  Embedding |  Responses |  bedrock-runtime |
|  Image |  Image |  Chat Completions |  bedrock-mantle |
|  Speech |  Speech |  Converse | |
|  Text |  Text |  Invoke | |
|  Video |  Video | | |
**Tip**
Whenever possible, we recommend using the `bedrock-runtime` endpoint for new applications. For Kimi K3, we recommend using the Chat Completions API. See [Endpoints supported by Amazon Bedrock](endpoints.md) for details.
## Capabilities and Features
***Bedrock Features***
**Features supported using `bedrock-runtime` endpoint**
| **Supported** | **Not Supported** |
| --- | --- |
| +  [Response streaming](/bedrock/latest/APIReference/API_runtime_InvokeModelWithResponseStream.html)
+  [Implicit Prompt Caching](prompt-caching.html#prompt-caching-implicit)
+  [Explicit Prompt Caching](prompt-caching.html#prompt-caching-explicit) (Responses and Chat Completions APIs only)
+  [Client-side tool calling](tool-use.html)
+  [Structured outputs](structured-outputs.html)
+  [Invocation logs](model-invocation-logging.html) | +  [Intelligent prompt routing](prompt-routing.html)
+  [Knowledge base](knowledge-base.html) |
**Explicit prompt caching using `bedrock-runtime` endpoint**
For more information, see [Prompt caching for faster model inference](prompt-caching.html).
| **Explicit Prompt Caching supported** | **Min tokens per cache checkpoint** | **Cache retention (TTL)** |
| --- | --- | --- |
| Yes | 1,024 | At least 30 minutes |
**Note**
By default, Kimi K3 supports implicit (automatic) prompt caching. Configuring explicit cache controls can improve your cache hit rate, and therefore reduce latency and cost, so we recommend using explicit prompt caching. Currently, only the Responses and Chat Completions APIs support explicit prompt caching. See the [prompt caching guide](prompt-caching.html) for more details.
## Pricing
| **Inference option** | **Input** | **Output** | **Cache read** | **Cache write (30 min)** |
| --- | --- | --- | --- | --- |
| Global CRIS | $3.00 | $15.00 | $0.30 | $3.75 |
| US CRIS | $3.30 | $16.50 | $0.33 | $4.125 |
*All prices are per 1 million tokens. Pricing shown is for the Standard tier.*
**Priority and Flex tier support:** In addition to Standard, Kimi K3 supports the Priority and Flex service tiers. Priority is billed at **1.75x** the Standard per-token rate (a 75% premium) and Flex at **0.5x** the Standard rate (a 50% discount); apply these multipliers to whichever Standard base rate (Global or US CRIS) applies to your request. For details on each service tier, see [service tiers](service-tiers-inference.html).
## Programmatic Access
Use the following model ID and endpoint URL to access this model programmatically. Kimi K3 is available through US Geo and Global cross-Region inference. For more information about the available APIs and endpoints, see [APIs supported](apis.html) and [Endpoints supported](endpoints.html).
| **Endpoint** | **Model ID** | **In-Region endpoint URL** | **Geo inference ID** | **Global inference ID** |
| --- | --- | --- | --- | --- |
| bedrock-runtime | moonshotai.kimi-k3 | https://bedrock-runtime.{region}.amazonaws.com | us.moonshotai.kimi-k3 | global.moonshotai.kimi-k3 |
*For example, if region is us-east-1 (N. Virginia), then the bedrock-runtime endpoint URL will be "https://bedrock-runtime.us-east-1.amazonaws.com".*
## Service Tiers
Amazon Bedrock offers multiple service tiers to match your workload requirements. **Standard** provides pay-per-token access with no commitment (set `"service_tier": "default"` or omit the field). **Priority** delivers the fastest response times for a price premium (set `"service_tier": "priority"`). **Flex** provides lower-cost access for flexible, non-time-sensitive workloads (set `"service_tier": "flex"`). For more information, see [service tiers](service-tiers-inference.html).
| **Standard** | **Priority** | **Flex** | **Reserved** |
| --- | --- | --- | --- |
|  |  |  |  |
**Note**
Currently, only the Responses and Chat Completions APIs support service tiers. The Converse and Invoke APIs do not support service tiers and support only Standard on-demand inference.
## Regional Availability
***Regional availability at a glance***
Amazon Bedrock offers three inference options: **In-Region** keeps requests within a single Region for strict compliance, **Geo Cross-Region** routes across Regions within a geography (such as US, EU, and APAC) while respecting data residency, and **Global Cross-Region** routes anywhere worldwide when there are no residency constraints. Refer to the [Regional availability by models](models-region-compatibility.md) page for more details.
Kimi K3 is available through US Geo cross-Region inference (using the `us.moonshotai.kimi-k3` profile, which routes requests only among US-geography Regions to respect US data residency) and Global cross-Region inference (using the `global.moonshotai.kimi-k3` profile, which routes to any supported commercial AWS Region worldwide). You choose the AWS Region you send requests to, and Amazon Bedrock routes each request accordingly.
**Availability using the `bedrock-runtime` endpoint**
| **Region** | **In-Region** | **Geo** | **Global** |
| --- | --- | --- | --- |
| us-east-1 (N. Virginia) |  |  |  |
| us-east-2 (Ohio) |  |  |  |
| us-west-1 (N. California) |  |  |  |
| us-west-2 (Oregon) |  |  |  |
| ca-central-1 (Canada) |  |  |  |
| ca-west-1 (Calgary) |  |  |  |
| eu-central-1 (Frankfurt) |  |  |  |
| eu-central-2 (Zurich) |  |  |  |
| eu-north-1 (Stockholm) |  |  |  |
| eu-south-1 (Milan) |  |  |  |
| eu-south-2 (Spain) |  |  |  |
| eu-west-1 (Ireland) |  |  |  |
| eu-west-2 (London) |  |  |  |
| eu-west-3 (Paris) |  |  |  |
| ap-east-2 (Taipei) |  |  |  |
| ap-northeast-1 (Tokyo) |  |  |  |
| ap-northeast-2 (Seoul) |  |  |  |
| ap-northeast-3 (Osaka) |  |  |  |
| ap-south-1 (Mumbai) |  |  |  |
| ap-south-2 (Hyderabad) |  |  |  |
| ap-southeast-1 (Singapore) |  |  |  |
| ap-southeast-2 (Sydney) |  |  |  |
| ap-southeast-3 (Jakarta) |  |  |  |
| ap-southeast-4 (Melbourne) |  |  |  |
| ap-southeast-5 (Malaysia) |  |  |  |
| ap-southeast-6 (New Zealand) |  |  |  |
| ap-southeast-7 (Thailand) |  |  |  |
| il-central-1 (Tel Aviv) |  |  |  |
| me-central-1 (UAE) |  |  |  |
| me-south-1 (Bahrain) |  |  |  |
| af-south-1 (Cape Town) |  |  |  |
| sa-east-1 (São Paulo) |  |  |  |
## Quotas and Limits
Your AWS account has default quotas to maintain the performance of the service and to ensure appropriate usage of Amazon Bedrock. The default quotas assigned to an account might be updated depending on regional factors, payment history, fraudulent usage, and/or approval of a quota [increase request](quotas-increase.html). See your default quotas in Service Quotas and request limit increases as necessary.
## Usage Considerations and Limitations
+ **Prefer the OpenAI-compatible APIs over Converse** — Although Kimi K3 can be called through the Converse and ConverseStream APIs, we recommend using the OpenAI-compatible Responses or Chat Completions APIs where possible. Converse has known limitations with this model, including a failure (`InternalServerException`) when reasoning content from earlier turns is included in a multi-turn request, which affects frameworks such as LangChain and Strands Agents in their default configurations, and rejection of attached document inputs such as PDF and HTML. To use Converse for multi-turn requests, remove reasoning blocks from prior turns.
+ **Video inputs are not supported** — Amazon Bedrock does not support attaching video inputs to Kimi K3 requests.
+ **Place images before text for combined inputs** — For requests that combine text and images, Kimi K3 can produce higher-quality answers when image content blocks are placed before text content blocks. This behavior is prompt-dependent, so test both orderings for your own workload.
+ **Image detail parameter** — The `detail` parameter that controls image input fidelity (`low` for lower cost or `high` for higher-fidelity understanding) is honored only on the Chat Completions API. On the Responses API, images are always processed at high detail.
## Sample Code
**Step 1 - AWS Account:** If you have an AWS account already, skip this step. If you are new to AWS, sign up for an [AWS account](https://portal.aws.amazon.com/billing/signup).
**Step 2 - API key:** Go to the [Amazon Bedrock console](https://console.aws.amazon.com/bedrock/home#/api-keys/long-term/create) and generate a long-term API key.
**Step 3 - Get the SDK:** To use this getting started guide, you must have Python already installed. Then install the relevant software depending on the APIs you are using.
------
#### [ Responses / Chat Completions API ]
```
pip install -U openai aws-bedrock-token-generator
```
------
#### [ Invoke/Converse API ]
```
pip install boto3
```
------
**Step 4 - Run your first inference request:** Save the file as `bedrock-first-request.py`
------
#### [ Responses API ]
```
from aws_bedrock_token_generator import provide_token
from openai import OpenAI
region = "us-west-2"
client = OpenAI(
api_key=provide_token(region=region),
base_url=f"https://bedrock-runtime.{region}.amazonaws.com/openai/v1",
)
resp = client.responses.create(
input="Can you explain the features of Amazon Bedrock?",
model="global.moonshotai.kimi-k3",
)
print(resp.output_text)
```
------
#### [ Converse API ]
```
import boto3
client = boto3.client('bedrock-runtime', region_name='us-west-2')
response = client.converse(
modelId='global.moonshotai.kimi-k3',
messages=[
{
'role': 'user',
'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
}
]
)
print(response)
```
------
#### [ Invoke API ]
```
import json
import boto3
client = boto3.client('bedrock-runtime', region_name='us-west-2')
response = client.invoke_model(
modelId='global.moonshotai.kimi-k3',
body=json.dumps({
'messages': [{ 'role': 'user', 'content': 'Can you explain the features of Amazon Bedrock?'}],
'max_tokens': 1024
})
)
print(json.loads(response['body'].read()))
```
------