Microsoft has worked closely with XAI to bring Grok 4, their most advanced model, to Azure AI Foundry-calls a powerful justification within the platform for safety and inspection ready for business.
Today’s companies are entering the new AI adoption phase – where trust, flexibility and production readiness are not optional; Are the basic. Microsoft worked closely with XAI to bring GROK 4Their most advanced model, at the Azure Ai-Foundry foundry, a powerful justification within the platform for safety and inspection ready for business.
GROK 4 undeniably has exceptional performance. With the 128K-T-Cen context window, using a native tool and integrated search on the web, it shifts the boundaries of what can be in contextual reasoning and generating a dynamic response. But the performance itself is not enough. AI must also be responsible on the border. Over the last month of XAI and Microsoft, they have worked closely to strengthen the responsible design. The team evaluated from the responsible perspective of AI and GROK 4 through a set of security tests and inspections of compliance. The safety of the Azure AI content is on by default and adds another layer of protection for the use of the company. For more information about the safety of the model, see Foundry Model.
In this blog we will explore what Grok 4 stands out, as compared to other frontier models and how developers can approach it through the Azure AI foundry.
GROK 4: Improved justification, extended context and real -time knowledge
GROK models have been trained on XAI Colossus supercomputers, using a massive computational infrastructure that XAI claims to bring 10 times a scrape of training compared to GROK 3. GROK 4 architecture refers to significant shift from its predecessors and emphasizes learning (RL) and more systems. According to the XAI, the model prefers to think about traditional pre -training, with a large focus on RL to clarify its ability to solve problems.
Key architectural main data include:
Justification of the first principles: “Think Mode”
One of the main features of Grok 4 is its The ability to justify the first principles. Basically, the model is trying to “think” as a scientist or a detective and step after step interleaves problems. Instead of a grok 4, Grok 4 can go through the logic internally and improve her answer. He has a strong knowledge of mathematics (solving competitive problems), science and humanities. The first users noticed that they excel in logical puzzles and fine justification better than some existing models, often looking for the right answers where others are confused. Simply put, Grok 4 is not just appeal Information – actively reasons through problems. Thanks to this focus on logical consistency, it is particularly attractive if your use requires step by step (think about research analysis, tutoring or a complex problem solution).
Example of challenge: Explain how you would generate electricity on Mars if you didn’t have an existing infrastructure. Start from the first principles: What are the basic resources, restrictions and physical laws you would use?
An extended context window
Perhaps one of the most impressive GROK 4 technical performance is handling extremely large contexts. The model is created to process and remember a huge amount of text at once. From a practical point of view, this means that Grok 4 can receive extensive documents, lengthy research documents or even a large code base and then justify them without shortening or forgetting earlier parts. In case of use as:
- Document Analysis: You could feed on hundreds of document pages and ask GROK to summarize, find irregularities or answer specific questions. Grok 4 is a much less likely to miss the details simply because they have reached the context window compared to other models.
- Research and academic community: Load the entire edition of the academic diary or a very long historical text and let it analyze or answer questions throughout the text. For example, it could take all Shakespeare games and answer a question that requires connection information from multiple games.
- Storage code: Developers could enter the entire code storage or more files (up to millions of code characters) and ask GROK 4 to find out where the function is defined or detect errors across the code base. This is huge for understanding large inheritance projects.
Xai claimed it was not just “memory”, but “intelligent memory”. Grok can intelligently compress or prefer information in very long input inputs and more strongly remember key pieces. It is with you for an end user or developer: Grok 4 can handle very large entry texts in one shot. This reduces the need to chop documents or encode and manage context fragments manually. You can use a ton of information to do this and can have the whole thing in mind how it reacts.
Example of challenge: Read this Shakespeare game and find my password (the password is buried in a long context text).
Answers to data and real -time knowledge
Another force GROK 4 is how it can integrate external data sources into its responses and trend information-in need effectively acts as a data analyst or real-time researcher. Understands that sometimes must be the best answer outside Its training data and has mechanisms to load and integrate these external data. It will turn Chatbot into a more autonomous research assistant. You ask the question, you can read a few things online and return with the answer that is enriched with real data. Of course, caution is required – Liva data can sometimes be incorrect or the model could be picked up on distorted sources; One should verify critical outputs.
Example of challenge: Check the latest AI global reports (last 48 hours).
- Summarize Top 3 Development.
- Emphasize which regions or government control changes.
- Explain what the impact of these updates could have on companies deploying models of the foundation.
- Provide referenced sources.
Grok 4 stacking: How does it work against top models
Grok 4 represents impressive skills at high tasks. These standards emphasize the top GROK 4 capabilities in a high level, STEM discipline, complex problems and tasks specific to the industry. These reference numbers are calculated using our own Azure AI Foundry Benchmarking Service, which we use to compare models across the set of industrial standard benchmarks.
GROK Family
In addition to the GROK 4, the Azure AI Foundry also has 3 other GROK models.
- Grok 4 Rapid thinking is optimized for tasks requiring logical inference, problem solving and comprehensive decision -making, which is ideal for analytical applications.
- Grok 4 Fast not justified focuses on speed and efficiency for direct tasks such as summary or classification, without deep logical processing.
- Grok Code Fast 1 is adapted specifically for generating and tuning code and excels in tasks related to programming across several languages.
While all three models prefer speed, their strengths differ: the justification of logically heavy tasks, not justified for light operations and the code for developers’ workflows.
Prices including Azure AZ Contents:
| Model | Deploymenttype | Price $/1m tokens |
| GROK 4 | Global standard | Input – $ 5.5 Output – $ 27.5 |
Start with Grok 4 in Azure AI Foundry
Guidance with inspection, be confidently. Grok 4 unlocks the reasoning at the level of border and intelligence in the real period, but it is not a model of deployment and forgotten. Pair the Azure railing with your own domain checks, monitor the outputs against developing standards and responsibly iterate – while we continue to stiffen the model and publish a new safety score. For more information about the safety of the model, see the Azure AI Foundry Grok 4.
Go to ai.azure.com, look for “Grok” and start examining what these powerful models can do.
(Tagstotranslate) Models of large languages (LLM)