Scalable Human Blog

TL;DR:
xAI’s /v1/chat/completions endpoint for Grok offers OpenAI-compatible chat generation with support for text and image inputs, real-time search, and unique parameters like reasoning_effort. While it mirrors OpenAI’s structure closely, it introduces distinct capabilities that set it apart from competitors like Gemini and Anthropic.

When xAI introduced Grok, it entered the AI chat landscape with a bold proposition: blend OpenAI-style compatibility with real-time search and multimodal support. The /v1/chat/completions endpoint is Grok’s primary API for generating conversational responses, and it’s designed to be familiar to developers already using OpenAI’s tools. But beneath that surface-level similarity are some powerful tweaks and unique features that make Grok worth a closer look.

In this guide, we’ll explore how to use Grok’s chat endpoint, the key parameters you can tune, and how it stacks up against OpenAI, Google Gemini, and Anthropic.

Grok’s Chat Endpoint: Familiar Yet Feature-Rich

The /v1/chat/completions endpoint is Grok’s main interface for generating responses from models like grok-beta or grok-4. It supports both text and image inputs, making it suitable for multimodal applications. Structurally, it mirrors OpenAI’s /v1/chat/completions endpoint, which means developers can often switch with minimal code changes.

The endpoint accepts a list of messages, each with a role (system, user, or assistant) and content, which can include both text and images. This makes it ideal for building chatbots, assistants, and other interactive AI tools.

Key Parameters You Can Tweak

Grok supports a wide range of parameters—many of which will feel familiar to OpenAI users—with a few unique additions.

Required Parameters:

• model: Choose between grok-beta, grok-1, or grok-4.
• messages: Array of message objects with role and content. Supports text and image parts.

Optional Parameters:

• max_tokens: Limits the length of the response.
• temperature (0–2): Controls randomness. Higher values = more creative.
• top_p: Alternative to temperature for sampling diversity.
• stream: Enables real-time streaming of responses.
• n: Number of completions to generate.
• stop: Stop sequences to cut off responses.
• frequency_penalty / presence_penalty: Helps avoid repetitive outputs.
• tools / tool_choice: Enables function calling, similar to OpenAI’s tool use.

Grok-Specific Parameters:

• search_parameters: Enables live search, a standout feature. You can specify max_results, from_date, and to_date to control the scope.
• reasoning_effort: Accepts low or high. Available in some models (not grok-4) to adjust the depth of reasoning.

For developers using Node.js, the OpenAI SDK works out of the box by setting the base URL to https://api.x.ai/v1. Here’s a quick example:

const { OpenAI } = require('openai');

const openai = new OpenAI({
  apiKey: 'your-xai-key',
  baseURL: 'https://api.x.ai/v1',
});

const response = await openai.chat.completions.create({
  model: 'grok-beta',
  messages: [{ role: 'user', content: 'What’s the latest news on AI?' }],
  search_parameters: { max_results: 3 },
});

How Grok Compares to OpenAI, Gemini, and Anthropic

🔁 OpenAI Compatibility
Grok is nearly a drop-in replacement for OpenAI’s API. The parameter names, endpoint structure, and even function calling via tools are all aligned with OpenAI’s chat API. This makes migration incredibly smooth.

📸 Gemini Differences
Unlike Grok, Google’s Gemini API uses a generateContent endpoint with contents and parts instead of messages. Gemini also includes safetySettings to manage output appropriateness, which Grok lacks. However, Grok introduces search_parameters, which Gemini doesn’t support (Gemini relies on cachedContent instead of live search).

🧠 Anthropic Contrasts
Anthropic’s Claude models use a different structure entirely. Their messages API separates the system role from the message list and includes parameters like top_k and stop_sequences that Grok doesn’t support. However, Grok’s reasoning_effort and real-time search offer unique advantages in applications requiring deeper or more current insights.

🧳 Portability
If you’re already using OpenAI, Grok is the easiest to switch to. Gemini and Anthropic require more structural changes in how you format inputs and handle outputs.

Key Takeaways

• OpenAI-Compatible: Grok’s API structure mirrors OpenAI’s, making integration straightforward.
• Real-Time Search: search_parameters enables live web search, ideal for current events.
• Multimodal Support: Input can include both text and images.
• Unique Controls: reasoning_effort adds depth control not found in other APIs.
• Enterprise Preview: The API is currently in preview and requires a Bearer token for authentication.

Conclusion

Grok’s /v1/chat/completions endpoint brings the best of both worlds: OpenAI-style ease of use and unique capabilities like real-time search and adjustable reasoning depth. While it doesn’t drastically reinvent the wheel, it adds meaningful features that can give your AI applications an edge—especially if you need up-to-date information or multimodal inputs.

If you’re building with OpenAI and looking for alternatives, Grok offers a low-friction path to experimentation. Try it out via the xAI API Console, and start tweaking parameters to see how Grok handles your most complex prompts.

Have you tested Grok in your stack? Share your experience or ask questions in the comments below!

📚 Further Reading & Related Topics
If you’re exploring Grok’s Chat Completions Endpoint and how it compares to OpenAI, Gemini, and Anthropic, these related articles will provide deeper insights:

• Grok 3 Major Release Highlights 2025 – This post dives into the major updates in Grok 3, offering valuable context for understanding how its chat completions have evolved and how they stack up against competitors.

• Understanding Roles and Maintaining Context in the OpenAI Chat Completion API: A Prompt Engineer’s Guide – A detailed look at how OpenAI handles roles and conversation context, which is essential for comparing the nuances of Grok’s implementation.

• Optimizing OpenAI API Prompt Configuration with SpringAI: A Guide to Parameters and Best Practices – This guide explains key parameters in OpenAI’s API, offering a useful reference point for evaluating Grok’s parameter design and performance.