What is Grok 4.5?

Grok 4.5 is an advanced AI model from SpaceXAI built for coding, agentic tasks, engineering workflows, and knowledge work. It is presented as SpaceXAI’s strongest model to date and is designed to perform well on real-world software engineering tasks rather than only short benchmark prompts. The model was trained on datasets spanning coding, science, engineering, and math, with heavy investment in data filtering, deduplication, quality scoring, and domain-focused selection. Its reinforcement learning process focuses on multi-step software engineering, technical problem solving, automated grading, model-based evaluation, and long-running agentic rollouts. Grok 4.5 can work on challenging development tasks across languages and environments, including Rust, C/C++, terminal workflows, debugging, bug fixing, and end-to-end app generation. The model is also capable of building polished applications from a single prompt, such as interactive simulations, modern interfaces, and functional web experiences. In addition to coding, Grok 4.5 supports knowledge work inside Grok Build, including Excel model creation, web research, multi-sheet formulas, PowerPoint slide design, native diagram creation, and Word document drafting. It is designed for speed and efficiency, with fast serving, strong token efficiency, and pricing based on input and output token usage. Developers can access Grok 4.5 through the SpaceXAI API console, Cursor, and Grok Build, making it usable across coding tools, productivity environments, and custom applications. The model is positioned for teams that need intelligent technical execution at a lower cost and with fewer steps than some competing frontier models. By combining engineering-focused training, agentic reasoning, fast inference, office productivity skills, and broad developer access, Grok 4.5 gives users a capable model for building, automating, debugging, researching, and shipping complex work.

Pricing

Price Starts At:
$2 per million input tokens
Price Overview:
$2 per million input tokens and $6 per million output tokens

Integrations

Offers API?:
Yes, Grok 4.5 provides an API

Screenshots and Video

Grok 4.5 Screenshot 1

Company Facts

Company Name:
SpaceXAI
Date Founded:
2023
Company Location:
United States
Company Website:
grok.com

Product Details

Deployment
SaaS
Training Options
Documentation Hub
Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

Grok 4.5 Categories and Features

Grok 4.5 Customer Reviews

Write a Review
  • Reviewer Name: A Verified Reviewer
    Position: Software Developer
    Has used product for: Less than 6 months
    Uses the product: Daily
    Org Size (# of Employees): 26 - 99
    Feature Set
    Layout
    Ease Of Use
    Cost
    Customer Service
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    Really big step up for Grok AI models

    Date: Jul 09 2026
    Summary

    Five stars from me. Grok 4.5 looks like a serious step forward for developers who are building AI agents, coding assistants, and automation-heavy workflows. The mix of coding strength, agentic focus, API availability, Cursor support, and lower-cost positioning makes it one of the more interesting models to build with right now.

    Positive

    Grok 4.5 is really impressive from the perspective of a developer and AI agent builder. It feels built for the stuff I actually care about: coding, tool use, agentic workflows, debugging, refactoring, and getting real work done instead of just chatting. I especially like that it seems focused on speed and cost efficiency, because those two things matter a lot when you are running agents over and over in production-like workflows.

    Negative

    It still feels early, and I would want to test it hard before trusting it as the backbone of serious production agents. Benchmarks and launch claims are useful, but they do not always translate perfectly into messy real-world codebases, weird edge cases, long-running tasks, and tool-heavy workflows. I also want to see how reliable it is across longer sessions, especially when an agent has to stay on track through multiple steps without drifting.

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