Grok 4.3 on Amazon Bedrock: The Mantle Endpoint Changes Everything You Know About Bedrock Integration

On June 15, 2026, xAI’s Grok 4.3 became available on Amazon Bedrock. The announcement is straightforward. The integration is not.

Grok 4.3 on Bedrock does not use the standard bedrock-runtime endpoint that every other Bedrock model uses. It does not support the Converse API. It does not support InvokeModel. It runs on a new infrastructure layer called Mantle — accessed via a completely different base URL — and it uses the OpenAI SDK rather than the AWS SDK for inference calls.

If you approach this like any other Bedrock model, you will hit errors immediately. This guide covers the actual architecture, the exact integration pattern, the reasoning configuration specifics, and how to decide whether Bedrock-hosted Grok is the right deployment path for your workload.

What “Mantle” Is

Amazon Bedrock launched a new inference engine alongside the Grok 4.3 integration called Mantle. AWS describes it as “designed for price performance,” but the more consequential detail is what it changes architecturally.

Standard Bedrock inference — the path used by Claude, Titan, Llama, Mistral, and every other model in the catalog — runs through bedrock-runtime.{region}.amazonaws.com. Authentication goes through IAM, requests use InvokeModel or the Converse API, and response formats follow Bedrock’s normalized schema.

Mantle is a separate endpoint entirely: bedrock-mantle.{region}.api.aws. It is not IAM-authenticated through the standard AWS credential chain in the same way. It uses a Bedrock-issued long-term API key, generated from the Bedrock console. And its path structure follows OpenAI’s API specification — specifically openai/v1/ — rather than Bedrock’s own schema.

In practice, Mantle is Amazon running an OpenAI-compatible inference endpoint that happens to be backed by Bedrock infrastructure. The authentication, the URL structure, and the SDK you use are all OpenAI-side conventions, not AWS conventions.

The Actual Model ID and Endpoint

Before anything else: the model ID is xai.grok-4.3, not grok-4.3 or xai/grok-4.3. The xai. prefix is how Bedrock namespaces third-party providers in its catalog.

The endpoint URL for us-west-2 (the only currently supported region):

https://bedrock-mantle.us-west-2.api.aws/openai/v1

Note the openai/v1 path. Other models on the Responses API use /v1/responses. Grok 4.3 on Mantle uses /openai/v1/responses. The openai/ prefix is required — omitting it returns a 404.

This is not a typo in the documentation. It is how Mantle routes requests to the xAI backend.

Getting Started: The Actual Integration

AWS provides straightforward setup steps. First, generate a long-term API key from the Amazon Bedrock console. This is different from standard AWS access keys — it is a Bedrock-specific key for Mantle endpoints.

Then configure the OpenAI SDK (not the AWS SDK):

pip install openai

Set environment variables:

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

Chat Completions API:

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="xai.grok-4.3",
    messages=[
        {"role": "user", "content": "Review this contract clause for jurisdiction ambiguity."}
    ]
)
print(response.choices[0].message.content)

Responses API:

from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model="xai.grok-4.3",
    input="Review this contract clause for jurisdiction ambiguity."
)
print(response.output_text)

The Responses API is the recommended path for reasoning-aware workloads, because only the Responses API returns reasoning tokens and supports encrypted reasoning content for multi-turn context.

Reasoning Configuration

Grok 4.3 on Bedrock has reasoning always-on. The default effort level is low. This is not the same as no reasoning — low effort means the model is thinking before every response, which increases latency and token cost relative to a non-reasoning model.

The four effort levels:

Level	Behavior
`none`	Disables reasoning entirely. Fastest, lowest cost. Behaves like a standard completion model.
`low`	Default. Light reasoning on every response.
`medium`	Deeper chain-of-thought. Noticeably slower. Use for complex analysis tasks.
`high`	Maximum reasoning effort. Significant latency. Use for high-stakes single-turn tasks.

To override the default:

response = client.responses.create(
    model="xai.grok-4.3",
    reasoning={"effort": "high"},
    include=["reasoning.encrypted_content"],
    input="Analyze this credit agreement for cross-default provisions."
)

The include=["reasoning.encrypted_content"] parameter tells Bedrock to return the reasoning trace in encrypted form. You can pass this encrypted content back in subsequent turns to give the model context on how it reasoned in previous steps — useful for multi-step analysis tasks where you want consistent reasoning continuity.

Important: The Chat Completions API does not return reasoning tokens at all. If you need to inspect or loop back reasoning content, use the Responses API.

To fully disable reasoning:

response = client.chat.completions.create(
    model="xai.grok-4.3",
    messages=[{"role": "user", "content": "Summarize this document."}],
    extra_body={"reasoning": {"effort": "none"}}
)

Default Parameter Differences

Grok 4.3 on Bedrock uses defaults that differ from the OpenAI API specification. If you are porting code from an OpenAI integration without explicit parameter setting, these differences will affect output behavior:

Parameter	OpenAI default	Grok 4.3 on Bedrock default
`temperature`	1.0	0.7
`top_p`	1.0	0.95
`max_completion_tokens`	model-defined	131,072

The lower temperature default means outputs will be less random than what you get from GPT-4o or Claude at their defaults. If you are running deterministic or precision-sensitive tasks, temperature: 0.7 may actually be preferable. If you are running creative or varied-output tasks, explicitly set temperature higher or you will get more uniform outputs than intended.

Capabilities: What Is and Is Not Available

Grok 4.3 on Bedrock via Mantle supports:

Text input ✓
Image input ✓
Text output ✓
Chat Completions API ✓
Responses API ✓
Tool calling ✓
Structured output ✓
Response streaming ✓

Grok 4.3 on Bedrock does not support:

Audio input/output ✗ — the native xAI API supports voice cloning; Bedrock does not
Video input ✗ — Grok 4.3 has native video input capability on the xAI API; not available on Bedrock
Embedding output ✗
Converse API ✗ — the standard Bedrock multi-provider abstraction does not work
InvokeModel ✗ — the standard Bedrock invocation API does not work
bedrock-runtime endpoint ✗ — you must use the Mantle endpoint
Global or Geo cross-region inference ✗ — us-west-2 in-region only for now
Reserved throughput ✗

The audio and video gaps matter if you are evaluating Grok 4.3 as a replacement for multimodal workloads. The Bedrock deployment is specifically a text-and-image reasoning path. Voice cloning and video input require the native xAI API.

The Converse API gap is significant if you have an existing multi-provider Bedrock deployment that routes through Converse to abstract over Claude, Titan, and others. Adding Grok 4.3 to that abstraction layer is not currently possible. You would need a separate integration path specifically for Grok.

Service Tiers

Bedrock’s four inference tiers are partially available:

Standard — Pay-per-token. No commitment. ✓
Priority — Higher throughput with a time-based commitment. ✓
Flex — Lower cost for flexible, non-time-sensitive workloads. ✓
Reserved — Dedicated throughput with a term commitment. ✗

The absence of Reserved throughput means you cannot provision committed capacity for Grok 4.3 on Bedrock at this point. For workloads that need SLA-backed throughput guarantees, the native xAI API with its Priority Processing tier (launched June 15 for direct API customers) may be a better path.

Bedrock-Native vs. xAI-Direct: When to Choose Each

The decision is not about capability parity — it is about where your existing infrastructure lives and what compliance requirements you have.

Reasons to use Grok 4.3 on Bedrock:

Your workload already runs on AWS infrastructure with IAM-bounded access control
You need enterprise compliance artifacts: VPC endpoints, AWS PrivateLink, CloudTrail audit logs, service control policies
You are billing AWS usage to a centralized account with consolidated invoicing
Your procurement team has an AWS enterprise agreement that covers third-party models on Bedrock
You want AWS-side data residency commitments for us-west-2 processing

Reasons to use the native xAI API:

You need audio input/output or video input capabilities
You are already on the xAI API for other Grok models and want one credential to manage
You need global cross-region routing, not just us-west-2
Your team runs Grok Build (the xAI coding agent) and wants API consistency
You are evaluating Grok V9-Medium when it ships to API — it will appear on the native xAI API first

The native xAI API pricing for Grok 4.3 is $1.25/$2.50 per million input/output tokens. Bedrock adds its own markup on top of model cost — check the Amazon Bedrock Pricing page for current Mantle rates, which may vary.

The SpaceX/xAI Context

The Bedrock launch happened three days before SpaceX filed its binding merger agreement with Cursor on June 16. The timing is coincidental — the Bedrock integration predates the merger filing by weeks of infrastructure work — but the acquisition context is relevant for the longer-term deployment picture.

Post-acquisition, xAI’s model distribution strategy shifts. Cursor gives xAI direct IDE distribution to 4+ million active developers. Bedrock gives it enterprise distribution through AWS’s enterprise sales channel. These are complementary paths: consumer developers through Cursor, enterprise builders through Bedrock, direct API users through api.x.ai.

Grok V9-Medium, the 1.5-trillion-parameter coding model expected in the June 15–25 window on the native xAI API, has not appeared on Bedrock documentation as of June 18. When it does, expect the same Mantle-endpoint architecture.

Summary for Builders

Three things to internalize before you start:

Use the OpenAI SDK, not the AWS SDK. The Mantle endpoint is OpenAI-compatible. boto3.client('bedrock-runtime') will not work.
Reasoning is always-on at low effort by default. If you want no reasoning, pass {"effort": "none"} explicitly. If you want reasoning continuity across multi-turn conversations, use the Responses API and loop back encrypted reasoning content.
Check your default parameters. Temperature defaults to 0.7, not 1.0. If your existing prompts were calibrated for OpenAI-style defaults, outputs will be more conservative than expected until you adjust.

The Mantle endpoint is available now in us-west-2. More regions will follow.

Sources: AWS Bedrock Grok 4.3 model card | AWS What’s New — Grok on Bedrock | xAI Grok 4.3 builder guide

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