Grok 4 Fast (Non-reasoning)

For applications where every millisecond counts, prioritizing Microsoft Azure as your API provider is crucial. Azure consistently delivers the lowest latency and highest output speed for Grok 4 Fast.

• Prioritize Azure: Route high-priority, latency-sensitive requests through Azure to capitalize on its superior TTFT and tokens/s.
• Monitor Performance: Continuously monitor latency and throughput from both providers to ensure optimal routing and identify any performance degradation.
• Regional Deployment: Consider deploying Azure instances in regions geographically close to your user base to further minimize network latency.

Grok 4 Fast is exceptionally concise. By crafting prompts that encourage brief, direct answers, you can significantly reduce output token count and associated costs.

• Be Specific: Ask precise questions that require short, factual answers rather than open-ended queries.
• Use Constraints: Instruct the model to limit its response length (e.g., "in 50 words or less," "provide only the name").
• Iterate and Refine: Experiment with different prompt structures to find the most token-efficient way to achieve desired outputs.

With input tokens at $0.20/M and output tokens at $0.50/M, understanding this differential is key to cost management, especially for tasks with varying input/output ratios.

• Minimize Output Tokens: Since output tokens are 2.5x more expensive, focus efforts on reducing output verbosity where possible.
• Efficient Input Utilization: While input is cheaper, avoid sending unnecessarily large contexts. Use the 2M context window judiciously.
• Batch Processing: For tasks with large inputs and small outputs (e.g., summarizing many short documents), batching can amortize input costs more effectively.

The 2 million token context window is powerful but can be costly if not managed. Only include necessary information to keep input token counts down.

• Dynamic Context: Implement logic to dynamically adjust the context provided based on the current query's needs, rather than sending the full history every time.
• Summarize History: For long-running conversations, periodically summarize past interactions and inject the summary into the context rather than the raw transcript.
• Pre-processing: Filter or extract relevant information from large documents before feeding them to the model as context.

Regularly tracking your API usage and costs is fundamental to identifying inefficiencies and optimizing your spend.

• Implement Cost Tracking: Utilize provider-specific tools or third-party solutions to monitor token usage and expenditure.
• Identify High-Cost Workloads: Pinpoint specific applications or user behaviors that are driving up costs and target them for optimization.
• Set Budgets and Alerts: Establish spending limits and configure alerts to notify you when usage approaches predefined thresholds.

Grok 4 Fast (Non-reasoning) is an advanced AI model developed by xAI, optimized for speed and factual accuracy without performing complex logical reasoning. It excels in tasks requiring direct information retrieval, content generation, and summarization.

It scores 39 on the Artificial Analysis Intelligence Index, placing it significantly above the average of 28 for comparable models. This indicates strong performance in understanding and generating relevant, accurate information.

Grok 4 Fast boasts an average output speed of 144.6 tokens/s, with Microsoft Azure achieving up to 147 tokens/s. It also has an exceptionally low Time to First Token (TTFT) of 0.41 seconds via Azure, making it one of the fastest models available.

The model is priced at $0.20 per 1 million input tokens and $0.50 per 1 million output tokens. This competitive pricing positions it below the average costs for similar models, offering excellent value.

Our benchmarks include Microsoft Azure and xAI directly. Azure provides the best performance in terms of speed and latency, while both offer competitive pricing.

Grok 4 Fast supports both text and image inputs, allowing for multimodal applications. Its output modality is text, making it suitable for a wide range of content generation and information extraction tasks.

No, as its variant tag suggests, Grok 4 Fast is a "Non-reasoning" model. It is optimized for direct, factual responses and high-speed processing, not for tasks requiring multi-step logical deduction, complex problem-solving, or deep analytical reasoning.

Grok 4 Fast features a substantial 2 million token context window. This allows it to process and understand very large amounts of information within a single interaction, enabling sophisticated applications like long-document analysis or extended conversational contexts.