Grok 4.1 Fast (Non-reasoning)

High intelligence meets impressive speed and efficiency.

Grok 4.1 Fast (Non-reasoning)

A high-speed, highly intelligent, and concise model from xAI, offering a strong balance of performance and cost-efficiency for real-time applications.

High IntelligenceFastConcise2M ContextMultimodal InputxAI

Grok 4.1 Fast emerges from xAI as a formidable contender in the AI landscape, specifically engineered for applications where speed and responsiveness are paramount. Positioned as the high-velocity variant of their Grok series, this model is tailored for real-time interactions, such as sophisticated chatbots, live content generation, and rapid data summarization. It distinguishes itself not just by its speed but by maintaining a high level of intelligence, challenging the common trade-off between quick responses and cognitive depth. This unique combination makes it a compelling choice for developers looking to build fluid, engaging, and smart user experiences without the latency penalties often associated with top-tier models.

The performance metrics for Grok 4.1 Fast are impressive. It achieves a median output speed of 122.5 tokens per second, placing it comfortably above the class average of 93 tokens/s. This throughput is complemented by a low latency (time to first token) of just 0.52 seconds, ensuring that applications feel snappy and interactive. What truly sets it apart, however, is that this speed does not come at a significant cost to its intellectual capabilities. Scoring 38 on the Artificial Analysis Intelligence Index, it substantially outperforms the average score of 28 for comparable models. This indicates a strong ability to handle nuanced queries, generate coherent text, and perform complex instructions accurately, all while delivering results at a rapid pace.

From a cost perspective, Grok 4.1 Fast is positioned competitively. Its input price of $0.20 per 1 million tokens is slightly below the market average, while its output price of $0.50 per 1 million tokens also offers good value. A key, often overlooked, factor in its cost-effectiveness is its conciseness. During benchmark testing, the model generated only 6.5 million tokens to complete tasks where the average model produced 11 million. Because output tokens are 2.5 times more expensive than input tokens, this natural brevity can lead to significant cost savings in output-heavy applications. The total cost to run the comprehensive Intelligence Index benchmark on this model was a modest $15.38, underscoring its overall economic efficiency.

Beyond its core performance and pricing, Grok 4.1 Fast is equipped with cutting-edge technical specifications. It boasts a massive 2 million token context window, enabling it to process and analyze vast amounts of information—equivalent to entire novels or extensive code repositories—in a single pass. This capability unlocks powerful use cases in legal document review, research synthesis, and maintaining long-term memory in conversational AI. Furthermore, the model supports multimodal inputs, accepting both text and images. This allows for more versatile applications, such as analyzing visual data or answering questions about a supplied image, with the final output delivered as text. Currently available exclusively via the xAI API, it represents a powerful, self-contained ecosystem for developers.

Scoreboard

Intelligence

38 (17 / 77)

Scores 38 on the Artificial Analysis Intelligence Index, significantly outperforming the class average of 28.
Output speed

122.5 tokens/s

Faster than the average model in its class (93 tokens/s), making it ideal for real-time applications.
Input price

$0.20 / 1M tokens

Slightly more affordable than the class average of $0.25 for input tokens.
Output price

$0.50 / 1M tokens

Priced below the class average of $0.60 for output, offering good value for generated content.
Verbosity signal

6.5M tokens

Highly concise, generating significantly fewer tokens than the class average of 11M during evaluation, which helps control costs.
Provider latency

0.52 seconds

Quick to respond with a low time-to-first-token, enhancing the user experience in interactive sessions.

Technical specifications

Spec Details
Owner xAI
License Proprietary
Context Window 2,000,000 tokens
Input Modalities Text, Image
Output Modalities Text
API Provider xAI
Input Price $0.20 / 1M tokens
Output Price $0.50 / 1M tokens
Blended Price (3:1) $0.28 / 1M tokens
Median Latency (TTFT) 0.52 seconds
Median Output Speed 122.5 tokens/second

What stands out beyond the scoreboard

Where this model wins
  • Blazing Speed: Delivers an exceptionally high output speed of 122.5 tokens/s with low latency, making it a top choice for chatbots, live summarization, and other real-time use cases.
  • High Intelligence: Despite its speed, it doesn't compromise on smarts, scoring a 38 on the Intelligence Index—well above many competitors in its speed and price class.
  • Cost-Effective Conciseness: Its tendency to be highly concise (generating 40% fewer tokens than average in tests) directly translates to lower costs on output-heavy tasks, amplifying its already competitive pricing.
  • Massive Context Window: A 2 million token context window allows for deep analysis of extensive documents, entire code repositories, or maintaining context over very long conversations.
  • Balanced Pricing: With input and output prices both below the class average, it provides a strong value proposition, especially when its high performance is considered.
Where costs sneak up
  • Output-Heavy Workloads: The 2.5x price multiplier for output tokens ($0.50) versus input tokens ($0.20) means that tasks generating significantly more text than they consume can become more expensive than they first appear.
  • Large Context Ingestion: While powerful, fully utilizing the 2 million token context window is not cheap. Ingesting a 2M token document would cost $0.40 per request, which can add up quickly if done frequently.
  • Image Input Ambiguity: The pricing for image inputs is not specified in this analysis. Multimodal applications could introduce a different and potentially significant cost vector that needs separate evaluation and budgeting.
  • Single Provider Lock-in: Being available only through xAI's API means there is no price competition. Users are subject to xAI's pricing structure and any future changes without alternative options.
  • 'Non-Reasoning' Limitations: The 'Non-reasoning' designation implies it may be less suitable for highly complex, multi-step logical problems compared to models explicitly tuned for reasoning, potentially requiring more prompt engineering or chained calls for such tasks.

Provider pick

Grok 4.1 Fast is currently available exclusively through its creator, xAI. This simplifies the choice of provider to a single option, but it also means that all users are tied to one source for API access, performance, and pricing. Your decision is not which provider to use, but whether the sole provider's offering fits your needs.

Priority Pick Why Tradeoff to accept
Top Performance xAI As the sole provider and creator, xAI offers direct, optimized access to the model's full capabilities, including its speed and massive context window. No alternative options for performance tuning, regional availability, or failover.
Lowest Price xAI The only available price point is the one set by xAI, making it the de facto cheapest (and most expensive) option. There is no ability to shop around for better rates, volume discounts, or different pricing models that might be offered in a competitive market.
Simplicity xAI With only one API to integrate, the development process is straightforward and documentation is centralized. Lack of provider-specific features, value-add services, or specialized support that might be offered by a competitive marketplace.

Performance and pricing data are based on benchmarks conducted by Artificial Analysis on the xAI API. As the model ecosystem evolves, other providers may become available, which could alter these recommendations.

Real workloads cost table

Theoretical prices per million tokens can be abstract. To understand the real-world financial impact of using Grok 4.1 Fast, let's model its cost across a few common application scenarios. These estimates use the benchmarked prices of $0.20/1M input tokens and $0.50/1M output tokens.

Scenario Input Output What it represents Estimated cost
Customer Support Chatbot 1,500 tokens (history) 200 tokens (response) A single turn in an ongoing support conversation. $0.0004
Email Summarization 2,000 tokens (email thread) 150 tokens (summary) Processing one long email for a user's inbox. $0.000475
Code Generation 500 tokens (description) 300 tokens (code) A developer requesting a simple utility function. $0.00025
RAG Document Query 8,000 tokens (query + context) 400 tokens (answer) Answering a question using a retrieval-augmented generation system. $0.0018
Large Document Analysis 100,000 tokens (report) 1,000 tokens (takeaways) A one-off analysis of a significant document. $0.025
Content Ideation 100 tokens (topic) 800 tokens (ideas list) Generating a list of blog post ideas from a single topic. $0.00042

The model's extremely low per-transaction cost makes it highly suitable for high-volume, interactive applications like chatbots. Costs become more noticeable only when processing very large inputs, but its natural conciseness helps keep output expenses in check across all workloads.

How to control cost (a practical playbook)

Grok 4.1 Fast's pricing is competitive, but costs can accumulate quickly in a production environment. A strategic approach to implementation is key to maximizing its value while managing your budget. Here are several strategies to consider to ensure cost-efficiency.

Lean into Conciseness

The model's greatest cost-saving feature is its natural brevity. Since output tokens cost 2.5x more than input tokens, every token you avoid generating is a direct saving. You can encourage this behavior further with careful prompting.

  • Explicitly ask for briefness in your prompts: Use phrases like "Be concise," "Summarize in three bullet points," or "Answer in a single sentence."
  • Set response format requirements: Requesting JSON output with specific fields can prevent the model from adding conversational filler.
  • Iterate on prompts to find the shortest effective wording that still elicits the correct response.
Optimize Context Window Usage

The 2 million token context window is a powerful tool, but filling it unnecessarily is a fast way to increase costs. For most tasks, a much smaller, targeted context is more efficient.

  • Implement a robust RAG (Retrieval-Augmented Generation) pipeline. Instead of feeding the model entire documents, use a vector search to find and provide only the most relevant chunks of text for answering a query.
  • For conversational memory, use summarization techniques. Periodically, have the model (or a cheaper, faster model) summarize the conversation history and use that summary as context for the next turn, rather than the full transcript.
  • Only use the large context window when the task absolutely requires it, such as analyzing a full legal contract or codebase for dependencies.
Cache Responses for Repeated Queries

Many applications receive identical or very similar user queries over time. Caching responses can eliminate redundant API calls and dramatically reduce costs.

  • Implement a semantic caching layer. Instead of exact-match caching, use vector embeddings to see if a new query is semantically similar to a previously answered one. If it is, you can serve the cached response.
  • For common questions (like in a FAQ chatbot), pre-generate and cache the answers to avoid hitting the API at all for known queries.
Monitor and Alert Aggressively

You cannot control what you cannot measure. Proactive monitoring is essential to prevent budget overruns, especially when scaling an application.

  • Utilize the dashboards provided by xAI to track your token consumption in near real-time.
  • Set up hard and soft budget alerts. A soft alert can warn you when you're at 50% of your monthly budget, while a hard alert can notify you when you're approaching your limit, giving you time to react.
  • Tag API calls with user or session IDs to identify which parts of your application are consuming the most tokens. This can help you find areas for optimization.

FAQ

What is Grok 4.1 Fast?

Grok 4.1 Fast is a large language model from xAI. It is a variant of the Grok 4.1 family, specifically optimized for high-speed output and low latency, making it ideal for real-time, interactive applications while still maintaining a high level of intelligence.

What does 'Non-reasoning' signify?

The 'Non-reasoning' tag suggests the model is tuned for fast, direct responses rather than complex, multi-step logical deduction. It excels at tasks like summarization, question-answering, and creative writing where a quick and coherent response is valued. It may be less suited for intricate problem-solving that requires deep, sequential thought, which is likely the domain of a corresponding 'Reasoning' model.

How does its 2M token context window help?

The 2 million token context window allows the model to process and 'remember' a vast amount of information within a single request. This is equivalent to roughly 1.5 million words. It enables powerful use cases like analyzing an entire book, a large codebase, or a lengthy financial report in one go, allowing for deep synthesis and cross-referencing of information.

Is Grok 4.1 Fast multimodal?

Yes, it is multimodal on the input side. It can accept both text and images as part of a prompt. However, its output is limited to text only. This allows you to ask questions about an image or have it analyze visual information, but it will respond with a textual description or answer.

Who is the ideal user for this model?

The ideal user is a developer or business building applications that require a combination of high intelligence, low latency, and high throughput. This includes creators of advanced chatbots, real-time content generation tools, live data analysis systems, and any service where a fast, smart response is critical to the user experience.

Where can I access the Grok 4.1 Fast API?

Currently, Grok 4.1 Fast is available exclusively through the API provided by its creator, xAI. There are no other third-party providers offering access to this model at this time.


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