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The integration of Grok 4.3 into Amazon Bedrock highlights a strategic shift toward enterprise-grade model deployment, emphasizing cost-efficiency and reduced hallucination rates over raw parameter counts. This release underscores the industry's focus on practical utility for building AI agents, where configurable reasoning efforts and massive context windows directly address real-world operational constraints.
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Grok on Amazon Bedrock

xAI1 min read

Grok models are now available via Amazon Bedrock.

Today, we’re excited to announce that Grok 4.3 is now generally available on Amazon Bedrock.

Grok 4.3 achieves the lowest hallucination rate among frontier models, offers 1-million-token context window, and supports configurable reasoning efforts (none, low, medium, high). Now, Amazon Bedrock users can leverage the model through Bedrock’s secure and reliable inference engine.

Grok 4.3 is one of the strongest models available today for building enterprise-ready AI agents:

#1 on Artificial Analysis Omniscience benchmark*, achieving the lowest hallucination rate among frontier models.

#1 on Artificial Analysis Tau2 Telecom benchmark*, which evaluates real-world tool-calling performance in customer support agent scenarios.

#1 on Vals AI Case Law and Corporate Finance benchmarks, which measure Grok's capabilities in complex document understanding tasks.

Grok 4.3 sits on the Pareto frontier for intelligence versus cost, delivering 2-10x more intelligence per dollar than other frontier models.

Input: $1.25 per 1 million tokens

Output: $2.50 per 1 million tokens

It features a 1 million context window that handles extremely long documents and codebases with ease. Developers can also configure reasoning: Use none for maximum speed on simple requests, or low / medium / high to scale reasoning effort to the difficulty of the problem.

Build with Grok 4.3 on Amazon Bedrock

Grok 4.3 is now available to all developers in supported AWS Regions.

To get started, please visit the Grok on Amazon Bedrock documentation. We're excited to see what you build!

Full text under the publisher's open licence · 233 words

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