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📺 Info Siaran: bedrock/latest/userguide/model card xai grok .html - Info Live Streaming 2026
Icon showing the xAI logo. xAI — Grok 4.3Model DetailsCapabilities and FeaturesPricingProgrammatic AccessService TiersRegional AvailabilityQuotas and LimitsSample CodeUsage Considerations and Limitations

Grok 4.3

Icon showing the xAI logo. xAI — Grok 4.3

Model Details

Grok 4.3 is a reasoning-first model that offers always-on and configurable reasoning effort (none, low, medium, high). Because reasoning is always active rather than optional, it behaves more consistently across multi-step agent loops than models that can skip thinking. It also offers strong tool use and instruction-following capabilities for building multi-step agents, and token efficiency to help keep high-volume inference cost-effective. Grok 4.3 is especially well suited to enterprise workloads such as contract review, case law research, credit agreement analysis, and financial document Q&A, while delivering consistent, high-quality results across conversational AI, search, chat, and multi-turn workflows. Grok 4.3 runs on Mantle, a new inference engine in Amazon Bedrock designed for price performance, with support for tool calling, structured output, and response streaming.

  • Model launch date: June 15, 2026

  • Model EOL date: N/A

  • End User License Agreements and Terms of Use: View

  • Model lifecycle: Active

  • Context window: 1M tokens

  • Reasoning: Supported (configurable: none, low, medium, high)

Input Modalities Output Modalities APIs supported Endpoints supported
Red circle with white X icon indicating error, cancel, or close action. AudioRed circle with white X icon indicating error, cancel, or close action. EmbeddingGreen circle with white checkmark icon. Chat CompletionsRed circle with white X icon indicating error, cancel, or close action. bedrock-runtime
Green circle with white checkmark icon. ImageRed circle with white X icon indicating error, cancel, or close action. ImageGreen circle with white checkmark icon. ResponsesGreen circle with white checkmark icon. bedrock-mantle
Red circle with white X icon indicating error, cancel, or close action. SpeechRed circle with white X icon indicating error, cancel, or close action. SpeechRed circle with white X icon indicating error, cancel, or close action. Invoke
Green circle with white checkmark icon. TextGreen circle with white checkmark icon. TextRed circle with white X icon indicating error, cancel, or close action. Converse
Red circle with white X icon indicating error, cancel, or close action. VideoRed circle with white X icon indicating error, cancel, or close action. Video

On bedrock-mantle, this model is served at /openai/v1/responses, not the default /v1/responses.

Capabilities and Features

Bedrock Features

Features supported using bedrock-mantle endpoint

Supported Not Supported

—

Pricing

Inference option Input Output Cache read
In-Region$1.25$2.50$0.20

AWS GovCloud (US-West)

Inference option Input Output Cache read
In-Region$1.50$3.00$0.24

All prices are per 1 million tokens. Pricing shown is for the Standard tier. Grok 4.3 supports In-Region inference only.

Priority and Flex tier support: In addition to Standard, Grok 4.3 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 the Standard rates shown above. For details on each service tier, see service tiers.

Programmatic Access

Use the following model IDs and endpoint URLs to access this model programmatically. For more information about the available APIs and endpoints, see APIs supported and Endpoints supported.

Endpoint Model ID In-Region endpoint URL Geo inference ID Global inference ID
bedrock-mantle xai.grok-4.3 https://bedrock-mantle.{region}.api.aws/openai/v1 Not supported Not supported

For example, if region is us-west-2 (Oregon), then the bedrock-mantle endpoint URL will be "https://bedrock-mantle.us-west-2.api.aws/openai/v1".

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"). Reserved provides dedicated throughput with a term commitment for predictable workloads; it is set at the account level rather than per request (contact your AWS account team to enable). For more information, see service tiers.

Standard Priority Flex Reserved
Green circle with white checkmark icon. Green circle with white checkmark icon. Green circle with white checkmark icon. Red circle with white X icon indicating error, cancel, or close action.

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 page for more details.

Region In-Region Geo Global
us-west-2 (Oregon)Green circle with white checkmark icon.Red circle with white X icon indicating error, cancel, or close action.Red circle with white X icon indicating error, cancel, or close action.
us-east-1 (N. Virginia)Green circle with white checkmark icon.Red circle with white X icon indicating error, cancel, or close action.Red circle with white X icon indicating error, cancel, or close action.
us-east-2 (Ohio)Green circle with white checkmark icon.Red circle with white X icon indicating error, cancel, or close action.Red circle with white X icon indicating error, cancel, or close action.
us-gov-west-1 (GovCloud West)Green circle with white checkmark icon.Red circle with white X icon indicating error, cancel, or close action.Red circle with white X icon indicating error, cancel, or close action.

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. For more information, see Quotas for Amazon Bedrock documentation and see the limits for the model.

When consuming on-demand throughput on the bedrock-mantle endpoint, available throughput scales over time. Not all requests within your quota are guaranteed to succeed during periods of high demand, so ramping gradually is important. For this model, default limits aren't surfaced directly through Service Quotas, so we recommend following the ramp as your guide.

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.

Step 2 - API key: Go to the Amazon Bedrock console 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.

Chat Completions API
pip install openai
Responses API
pip install openai

Step 4 - Set environment variables: Configure your environment to use the API key for authentication.

Chat Completions API
OPENAI_API_KEY="<provide your Bedrock API key>"
OPENAI_BASE_URL="https://bedrock-mantle.us-west-2.api.aws/openai/v1"
Responses API
OPENAI_API_KEY="<provide your Bedrock API key>"
OPENAI_BASE_URL="https://bedrock-mantle.us-west-2.api.aws/openai/v1"

Step 5 - Run your first inference request: Save the file as bedrock-first-request.py

Chat Completions API
from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="xai.grok-4.3",
    messages=[
        {"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}
    ]
)
print(response)
Responses API
from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model="xai.grok-4.3",
    input="Can you explain the features of Amazon Bedrock?"
)
print(response)

Usage Considerations and Limitations

  • Reasoning effort — Reasoning is always active by default. You can configure effort through the reasoning parameter: {"effort": "none"} (disables reasoning), "low" (default), "medium", or "high". Reasoning content is encrypted and can be returned by passing include: ["reasoning.encrypted_content"] in the Responses API request. You can send the encrypted content back in subsequent turns to provide reasoning context for multi-turn conversations. The Chat Completions API does not return reasoning tokens.

    response = client.responses.create(
    model="xai.grok-4.3",
    reasoning={"effort": "high"},
    include=["reasoning.encrypted_content"],
    input="Explain quantum entanglement simply."
)
print(response.output_text)

  • Default parameters — Grok 4.3 uses defaults that differ from the standard OpenAI API specification: temperature defaults to 0.7 (not 1), top_p defaults to 0.95 (not 1), and max_completion_tokens defaults to 131072. Adjust these values explicitly if your application requires different behavior.