xAI Grok Review: Is It The Right Large Language Models (LLMs) For Your Team?
Best for SMB teams · Mid-market · Enterprise
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Starts from $1.00 / million input tokens
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What is xAI Grok?
xAI trains the Grok family and sells it through its own API, printing a rate per million tokens for every model in the public docs. The card uses two bands: one rate below 200,000 prompt tokens and a higher one at or above it, and a request that reaches the threshold is billed at the higher rate for all of its tokens. On the card read on 2026-11-08, grok-4.7, grok-4.6 and grok-4.5 are each 2.00 dollars per million input tokens and 6.00 per million output tokens under 200K, doubling to 4.00 and 12.00 above it. grok-4.3 is 1.25 and 2.50, and grok-build-0.1 is 1.00 and 2.00. A multi-agent model and separate image and voice products sit on the same account under their own units. Grok weights are not published, so the API is the route to these models.
Pricing
Starts from $1.00 / million input tokens
Best For
Suited for small teams, SMBs, and enterprise
Platform
Web-based — no mobile app
Browser Based (Cloud)
xAI Grok was reviewed internally using user feedback, in-house testing, and market research to assess its performance, reliability, and user experience. Learn how we review products and our evaluation process.
Who should consider xAI Grok
- Team types
- Small Business, Medium Business
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What is the pricing of xAI Grok?
xAI Grok Pricing Plans
grok-build-0.1
$1.00
per million input tokens
Input 1.00 dollars per 1M tokens under 200K prompt tokens
Output 2.00 dollars per 1M tokens
2.00 and 4.00 at or above 200K prompt tokens
grok-4.3
$1.25
per million input tokens
Input 1.25 dollars per 1M tokens under 200K prompt tokens
Output 2.50 dollars per 1M tokens
2.50 and 5.00 at or above 200K prompt tokens
grok-4.7
$2.00
per million input tokens
Input 2.00 dollars per 1M tokens under 200K prompt tokens
Output 6.00 dollars per 1M tokens
4.00 and 12.00 at or above 200K prompt tokens
Same rate on grok-4.6 and grok-4.5
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What are the features of xAI Grok?
Code generation produces source code from a higher-level input such as a natural language description, a specification, or an existing schem…
The context window is how much text, code or other input the model can hold in one request, counted in tokens, together with everything it h…
A language model is given descriptions of the functions or tools available to it and, when a request needs one, returns a structured call na…
The model accepts more than text in a single request: images, audio, video frames or documents alongside the prompt. Pricing is usually sep…
Storing the processed form of a prompt's repeated content, such as a long system instruction or a reference document, so that it does not ha…
The vendor prints a rate per million tokens on its own site, separately for the tokens a request reads and the tokens the model writes, so t…
The model can be asked to work through a problem step by step before answering, spending extra generated tokens on the working rather than t…
An interface that returns a model's output incrementally as it is produced, rather than waiting for the full response and sending it in one…
xAI Grok Support Options
Frequently Asked Questions About xAI Grok
Common questions buyers ask before choosing xAI Grok.
xAI Grok is a Large Language Models (LLMs). xAI Grok offers Published Token Pricing, Context Window, Function Calling, Streaming API, Prompt Caching and many more functionalities.
xAI Grok offers Subscription pricing model
The starting price of xAI Grok is $1.00/million input tokens
Ready to try it?
Get started with xAI Grok
Get connected with the team for a personalised demo.
About the reviewer
Rajat Gupta is the founder of Spotsaas, where he has built software research covering 25,000+ products across CRM, HR, AI, and finance. He applies hands-on product research and a background in commerce and the CFA program to evaluate software through a business and ROI lens. His goal: help teams make software decisions they won't regret.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].