Longer-running task performance
A larger base model and a longer reinforcement-learning run focused on difficult tasks that may take many hours to complete.
Grok 4.7 is an xAI model for coding and knowledge work, available via Grok Build, Cursor, the Grok API and more, from $2 per million input tokens.
Grok 4.7 is an AI model from xAI for software development and knowledge work. It is positioned for tasks that require sustained reasoning, including longer coding jobs, document and presentation creation, and professional workflows such as office, legal, clinical, electrical-engineering, and cybersecurity work.
Compared with Grok 4.6, the model uses a larger base model, longer reinforcement-learning training on harder tasks, and improved handling of extended context and self-checking. It is available through several developer and coding environments, including Cursor, Grok Build, the Grok API, third-party coding harnesses, model routers, and cloud platforms. The source lists token-based pricing starting at $2 per million input tokens and $6 per million output tokens, plus a faster variant at twice the output speed and twice the price.
A larger base model and a longer reinforcement-learning run focused on difficult tasks that may take many hours to complete.
Designed to check its own work more carefully, supporting workflows where intermediate results need review before completion.
Improved management of longer context, which is relevant to extended coding sessions and multi-step knowledge-work tasks.
Native understanding of the Grok Bot harness for conversational tasks and general knowledge work.
Benchmarked across software engineering, electrical engineering, office work, legal work, clinical reasoning, and cybersecurity-related tasks, with results differing by benchmark.
A new safeguard stack focused on refusal and jailbreak resistance. The source reports 62.4% on LatchBio’s biosafety benchmark and 3.3% of risky dual-use prompts allowed through on HackerBench v0.3, while emphasizing access to legitimate security work.
Use it for software-engineering tasks that run for extended periods, where longer context and more deliberate work checking can help maintain continuity across steps.
Apply it to multi-hour office work such as preparing professional documents and presentations. The source reports improvements over Grok 4.6 on GDPval and AA Briefcase benchmarks.
Use it as a general-purpose model for professional analysis across legal, clinical, and electrical-engineering tasks. Published benchmarks cover these areas, but results differ by task.
Use it for defensive cybersecurity research and legitimate security work. The model is designed to provide useful cyber capabilities while refusing risky or malicious dual-use requests.
Access it through Grok Build, Cursor, or an API-connected coding workflow depending on whether the task is exploratory, conversational, or integrated into developer tooling.
Grok 4.7 is available in Cursor and Grok Build, and it can also be accessed through the Grok API, third-party coding harnesses, model routers, and cloud platforms. The source page also provides links for creating an API key and reading the xAI documentation.
The model is available to try for free in Grok Build. The source does not specify the limits or conditions of that access.
The listed starting prices are $2 per million input tokens and $6 per million output tokens. A fast variant provides twice the output speed at twice the price; the source does not provide further plan or usage limits.
Grok 4.7 is intended for coding and knowledge work, including longer-running software tasks, document and presentation creation, office work, electrical engineering, legal work, clinical reasoning, and cybersecurity work. Benchmark results indicate that performance varies by task, so the model should be evaluated against the requirements of a specific workflow.
The model can work through the Grok Bot harness and is described as better at verifying its own work and managing longer context. The source does not specify particular file formats, output schemas, collaboration controls, or deployment requirements.
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