Grok 4.6
Grok 4.6 is SpaceXAI's frontier model for coding, long-running agents, knowledge work, and interactive visual projects.
Provider
SpaceXAI
Model family
xAI Grok
Frontier multimodal agentic LLM
Cost tier
Grok
Status
Current
Release Aug 12, 2026
Why teams choose it
The official API model ID is grok-4.6
with a 500K context window and low, medium, high, or xhigh reasoning effort.
SpaceXAI positions the release for sustained agent trajectories
coding, knowledge work, and polished interactive or visual artifacts.
Prompt cache keys and context compaction are important operational controls for long
tool-heavy conversations.
Tradeoffs to know
- Published benchmark results are vendor-reported and depend on reasoning effort and agent harness.
- Long contexts and xhigh reasoning can increase latency and cost; measure complete task economics rather than token price alone.
- Web, X search, code execution, and function tools require application-level permission and output validation.
Technical specs
- Inputs
- text, image
- Outputs
- text
- Capabilities
- coding, long-running agents, knowledge work, visual reasoning, function calling, web search, X search, code execution, configurable reasoning
- License
- Proprietary API
- Source
- https://x.ai/news/grok-4-6
- Deep Swe V1 1
- 65.9
- Cursorbench V3 2
- 69.9
- Aa Intelligence Index
- 61
- Frontier Code V1 1 Extended
- 61.3
Benchmarks
No independent or vendor benchmark scores in this catalog entry.
xAI Grok family lineup
Current models
Previous versions
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Grok 4.6 FAQ
What is Grok 4.6?
Grok 4.6 is SpaceXAI's frontier model for coding, long-running agents, knowledge work, and interactive visual projects. Official documentation lists text and image input, text output, a 500,000-token context window, configurable low through xhigh reasoning, function calling, web and X search, code execution, and the API model ID grok-4.6.
When does Grok 4.6 fit best?
Repository-scale coding agents
What should teams watch out for with Grok 4.6?
Published benchmark results are vendor-reported and depend on reasoning effort and agent harness.
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