xAI has rolled out a new Batch API for its Grok platform, targeting developers and organisations that handle large volumes of artificial intelligence tasks that do not need instant results.
The company said the update is designed for non-real-time workloads, allowing users to send large numbers of requests at once and have them processed over time. The move is aimed at reducing costs, increasing rate limits, and supporting large-scale AI operations that run in the background rather than live systems.
According to information shared by Elon Musk, the Batch API is suited for work such as nightly report generation, summaries, bulk document translation, large-scale question-and-answer tasks, embeddings at scale, and data processing that can be done offline.
xAI explained that by separating these types of workloads from real-time systems, teams can scale their AI use more smoothly while keeping systems stable.
Under the new setup, requests sent through the Batch API are processed asynchronously. Instead of receiving immediate responses, jobs are queued and handled over a period of time. This approach allows better use of computing resources and avoids overloading systems during peak usage.
The company said this model makes it easier for developers to manage offline workloads and data pipelines built on Grok, especially where large datasets are involved.
The Batch API supports multiple batches per team and is built to handle very high request volumes, while still applying limits to maintain stability. Each add-request payload can be up to 25MB, allowing developers to package large amounts of data into a single batch.
xAI said developers can manage the entire process through its SDK, including creating batches, adding requests, checking job status, cancelling tasks, and reviewing results in stages. This level of control is intended for production environments where tracking progress, handling errors, and stopping jobs when needed are essential.
The company said the update reflects growing demand from organisations that are embedding AI into everyday operations. Instead of focusing on chat-based or real-time uses, the Batch API is meant for background work such as processing historical data, running scheduled jobs, or supporting internal analytics systems.
In its guidance, xAI noted that the Batch API works best for large datasets, periodic processing tasks, and bulk requests. These use cases highlight the need for AI tools that fit into existing data systems rather than operating as standalone tools.
The launch also signals xAI’s wider goal of positioning Grok for full production use. By focusing on higher rate limits and lower costs, the company appears to be targeting teams moving beyond testing and into large-scale deployment.
While the announcement centres on technical features, it also points to competition in the AI space, where developers increasingly expect platforms to offer both real-time and batch processing options. For many organisations, such features are key to controlling costs and ensuring steady performance.
xAI described the update as “Grok built for real production workflows,” reinforcing its push toward industrial use cases rather than experimentation.
As AI use continues to grow across sectors, tools that support asynchronous, high-volume processing are becoming essential. With the Batch API, xAI is positioning Grok as a platform that can support both interactive applications and large-scale background processing without the limits of real-time systems.
