Amazon Bedrock Adds xAI’s Grok 4.7, Demonstrated Long‑Horizon Agent Performance
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Amazon Bedrock now offers the xAI Grok 4.7 model, featuring configurable inference intensity, tool‑calling capabilities, and structured output. In a recent AWS Machine Learning Blog test, Grok 4.7 achieved perfect scores on all 18 rounds of three search‑dependent tasks when run at high inference intensity. At low intensity, the model answered 15 of 18 rounds correctly, yet its output token count was roughly one‑eighth that of the high‑intensity runs. These results suggest that Grok 4.7 can maintain strong performance while significantly reducing token usage, potentially benefiting cost‑effective, long‑horizon agent applications on Bedrock. The demonstration highlights the trade‑off between inference intensity and output length, offering users flexibility in deploying the model for varied use cases.
Written with AI from the reporting · updated 10/14/2026
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New at this step ·SpaceXAI's Grok 4.7 Debuts on Amazon Bedrock with Enhanced Long-Horizon Agent Capabilities
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- AWS Machine Learning Blog · First-partySpaceXAI's Grok 4.7 Debuts on Amazon Bedrock with Enhanced Long-Horizon Agent CapabilitiesOriginal source ↗
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SpaceXAI's Grok 4.7 Debuts on Amazon Bedrock with Enhanced Long-Horizon Agent CapabilitiesAWS Machine Learning Blog
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- 1Oct 13, 00:00recorded Oct 14, 22:23single source
Build long-horizon agents with Grok 4.7 on Amazon Bedrock
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- AWS Machine Learning Blog · Oct 13, 23:52SpaceXAI's Grok 4.7 Debuts on Amazon Bedrock with Enhanced Long-Horizon Agent Capabilities
SpaceXAI's Grok 4.7, now on Amazon Bedrock, is designed for longer, more complex tasks, with improved self-checking capabilities. In tests, it achieved high accuracy in tasks requiring search, balancing accuracy and token usage effectively.
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- AWS Machine Learning BlogSelectedSpaceXAI's Grok 4.7 Debuts on Amazon Bedrock with Enhanced Long-Horizon Agent Capabilities
SpaceXAI's Grok 4.7, now on Amazon Bedrock, is designed for longer, more complex tasks, with improved self-checking capabilities. In tests, it achieved high accuracy in tasks requiring search, balancing accuracy and token usage effectively.