A high-performance model from xAI, delivering top-tier reasoning and remarkable speed at a competitive price point for demanding applications.
Grok 4 Fast (Reasoning) emerges from xAI as a formidable contender in the high-performance AI landscape, engineered to balance elite intelligence with exceptional speed. This model distinguishes itself not just by its raw capabilities but by its positioning as a cost-effective powerhouse. Scoring an impressive 60 on the Artificial Analysis Intelligence Index, it firmly plants itself in the top echelon of models, ranking 8th out of 134. This demonstrates a profound capacity for complex logic, nuanced understanding, and sophisticated problem-solving, making the "Reasoning" designation more than just a label—it's a promise of performance on demanding cognitive tasks.
Beyond its intellect, the model's defining characteristic is its speed. Clocking in at nearly 200 tokens per second on its native xAI platform, Grok 4 Fast is built for applications where latency is a critical factor. This velocity, combined with a low time-to-first-token, makes it an ideal engine for real-time conversational AI, interactive data analysis, and other use cases where immediate feedback is paramount. This performance is particularly noteworthy given its high intelligence score, as models in this class often trade speed for deeper processing. Grok 4 Fast challenges this convention, offering a rare combination of both.
Economically, Grok 4 Fast presents a compelling value proposition. With input and output token prices of $0.20 and $0.50 per million tokens respectively, it is competitively priced against other models of similar caliber. While not the absolute cheapest on the market, its blended cost is highly attractive for its performance tier. However, developers should be mindful of its tendency towards verbosity; it generated more than double the average number of tokens on our intelligence benchmark. This trait, coupled with an output price 2.5 times higher than its input price, requires careful management to prevent costs from escalating on generation-heavy tasks. The model's massive 2 million token context window further underscores this dual nature: immensely powerful for processing large documents, but a potential cost trap if not used judiciously.
Available through its native xAI API and Microsoft Azure, Grok 4 Fast offers developers a choice between raw, optimized performance and broad enterprise integration. The xAI endpoint delivers superior speed and lower latency, while Azure provides the benefits of its extensive cloud ecosystem. This dual-provider strategy makes the model accessible for a wide range of projects, from nimble startups building cutting-edge chat applications to large enterprises integrating advanced reasoning into their existing cloud infrastructure.
60 (#8 / 134)
197 tokens/s
$0.20 / 1M tokens
$0.50 / 1M tokens
61M tokens
3.91 seconds
| Spec | Details |
|---|---|
| Model Owner | xAI |
| License | Proprietary |
| Context Window | 2,000,000 tokens |
| Input Modalities | Text, Image |
| Output Modalities | Text |
| Architecture | Proprietary Transformer-based |
| Special Abilities | Real-time web access (Grok feature) |
| API Providers | xAI, Microsoft Azure |
| Base Model | Grok 4 |
| Intended Use | Complex reasoning, chat, RAG, agentic workflows |
| Fine-tuning | Not specified by provider |
Grok 4 Fast is available via its creator, xAI, and through Microsoft Azure. While the pricing is identical, the platforms serve different needs, creating a clear decision matrix based on your project's priorities. The choice is not about cost, but about the trade-off between raw performance and enterprise integration.
| Priority | Pick | Why | Tradeoff to accept |
|---|---|---|---|
| Raw Performance | xAI | The native API is measurably faster, with higher tokens per second (197 vs 168) and lower time-to-first-token (3.91s vs 5.55s). This is the best choice for latency-sensitive applications. | Lacks the deep integrations and consolidated billing of a major cloud provider like Azure. |
| Enterprise Ecosystem | Microsoft Azure | Integrates seamlessly with the entire Azure stack, including security, data storage, networking, and enterprise billing. Ideal for large organizations already invested in Azure. | Slower performance and higher latency compared to the native xAI API. You are trading speed for convenience. | Lowest Cost | Tie | Both providers offer identical pricing for input ($0.20/M) and output ($0.50/M) tokens. Cost is not a deciding factor between them. | Since price is the same, the decision must be based on other factors like performance, integration, or developer experience. |
| Simplicity & Direct Access | xAI | Provides a straightforward, direct-to-creator API. It's the quickest way to get started with the model without the overhead of a larger cloud platform. | Fewer peripheral services and potentially less robust support infrastructure compared to a global cloud provider. |
Provider performance metrics are based on our independent benchmarks. Your actual performance may vary based on workload, region, and other factors. Pricing is based on public information at the time of analysis and is subject to change.
To understand how Grok 4 Fast's pricing translates to practical application, we've estimated the cost for several common scenarios. These examples illustrate how the interplay between input and output tokens, combined with the model's verbosity, affects the final cost. All calculations use the standard pricing of $0.20 per 1M input tokens and $0.50 per 1M output tokens.
| Scenario | Input | Output | What it represents | Estimated cost |
|---|---|---|---|---|
| Customer Support Chatbot | 1,500 tokens | 500 tokens | A single, detailed turn in a support conversation, including chat history. | $0.00055 |
| Code Generation | 2,000 tokens | 1,500 tokens | Generating a new function based on existing code and detailed instructions. | $0.00115 |
| Long Document Summary | 100,000 tokens | 2,000 tokens | Condensing a lengthy report into a concise executive summary. | $0.021 |
| RAG-based Q&A | 4,000 tokens | 300 tokens | Answering a user query using retrieved document snippets for context. | $0.00095 |
| Multi-step Agentic Task | 20,000 tokens | 8,000 tokens | A complex workflow involving multiple steps of reasoning and action generation. | $0.00800 |
The takeaway is clear: Grok 4 Fast is highly affordable for interactive, chat-like tasks but costs scale with output. Input-heavy tasks like document summarization are cost-effective, while generation-heavy agentic workflows require careful monitoring of output token count to remain economical.
Managing the cost of a powerful model like Grok 4 Fast is crucial for building a sustainable application. Its specific characteristics—output-weighted pricing, high verbosity, and a massive context window—create unique opportunities for optimization. The following strategies can help you harness its power without breaking the bank.
Given that Grok 4 Fast tends to be verbose and its output tokens are 2.5x more expensive than input, controlling response length is the most direct way to manage costs. Modify your prompts to include explicit constraints.
Structure your application to minimize the number of tokens the model generates. Use Grok 4 Fast for what it excels at—reasoning and analysis—and rely on other methods for generating long-form, low-value text.
The 2 million token context window is a powerful tool, not a bucket to be filled indiscriminately. A full context prompt costs $400 in input alone. Smart context management is essential.
Many applications receive frequent, semantically similar queries. Implementing a cache can yield significant cost savings and performance improvements by avoiding redundant API calls.
Grok 4 Fast (Reasoning) is a large language model from xAI, optimized for a combination of high-speed performance and advanced reasoning capabilities. It is a variant of the Grok 4 family, designed for applications that require both quick responses and deep analytical power, such as complex chatbots, agentic systems, and real-time data analysis.
While specific benchmark comparisons are pending, the naming convention suggests a trade-off. Grok 4 Fast is likely optimized for lower latency and higher throughput (tokens per second), potentially at the cost of a slight reduction in maximum reasoning quality compared to a hypothetical, slower "Grok 4 Quality" model. It is designed for interactive use cases where speed is a primary concern.
The "Reasoning" tag indicates that this model has been specifically tuned and evaluated for tasks that require logical deduction, multi-step problem solving, and understanding complex instructions. Our benchmarks confirm this, with the model scoring in the top tier of our Intelligence Index, making it suitable for more than just simple text generation.
Yes, it is multimodal on input. Grok 4 Fast can accept both text and image data within its prompts, allowing it to perform tasks like describing an image, answering questions about a diagram, or interpreting visual information. However, its output is limited to text only.
The massive 2M token context window is a key feature for processing extremely large amounts of information in a single prompt. This is highly beneficial for:
However, due to the high cost, it should be used strategically, often in conjunction with RAG techniques.
Grok 4 Fast is ideal for developers and businesses that need a model that is both highly intelligent and very fast. It's a strong fit for customer-facing applications like advanced chatbots, internal tools for real-time data analysis, and agentic workflows that must execute quickly. Its competitive pricing also makes it attractive to those looking for a cost-effective alternative to other top-tier models.
The core model is the same, but the platform and performance differ. The xAI API offers the best performance, with higher speed and lower latency. The Microsoft Azure offering provides slightly lower performance but comes with the benefits of deep integration into the Azure cloud ecosystem, including enterprise-grade security, compliance, and consolidated billing. The choice depends on whether your priority is raw performance or seamless enterprise integration.