Grok 4.7

Grok 4.7

SpaceXSI
+
+

Related Products

  • LTX
    182 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • MicroStation
    593 Ratings
    Visit Website
  • kama.ai
    9 Ratings
    Visit Website
  • LendingPad
    302 Ratings
    Visit Website
  • AnalyticsCreator
    46 Ratings
    Visit Website
  • Screencapt
    140 Ratings
    Visit Website
  • NINJIO
    416 Ratings
    Visit Website
  • JAMS Scheduler
    285 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website

About

Grok 4.7 is a frontier AI model from SpaceXSI designed for coding, professional knowledge work, and longer-running agentic tasks. The model uses a larger base architecture than Grok 4.6 and was trained with an extended reinforcement learning process focused on difficult tasks that can take many hours to complete. Grok 4.7 improves self-verification, long-context management, conversational performance, and general knowledge work while adding native understanding of the Grok Bot harness. It is designed for software engineering, terminal-based work, document creation, presentations, legal tasks, electrical engineering, clinical reasoning, and other professional workflows. The model also introduces a new safeguard stack focused on jailbreak resistance, risky cybersecurity requests, and other dual-use domains while preserving utility for legitimate work. Grok 4.7 is available through Grok Build, Cursor, the Grok API, third-party coding harnesses, model routers, and cloud platforms.

About

Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Software developers, AI engineers, coding-agent builders, researchers, legal and technical professionals, and enterprises that need a high-capability model for complex coding, knowledge work, and long-running agentic tasks

Audience

AI developers, machine learning engineers, software engineers, AI researchers, enterprise development teams, and organizations seeking customizable open-weight multimodal models for local inference, autonomous agents, complex coding, and long-context AI applications

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$2 per 1M tokens (input)
$2 per million input tokens and $6 per million output tokens
Free Version Not Supported
Free Trial Not Supported

Pricing

$0
Model weights are available at no charge under the Muse Model License, which has limited commercial-use terms. Hosted inference providers set their own usage prices.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • The biggest improvement is how much better it is at sticking with longer tasks. It feels more deliberate than earlier Grok versions, especially when I am working through debugging, repo-level changes, or something that takes multiple rounds of planning and verification. The coding performance is strong too. xAI reports 46.3% on CursorBench 4.0 versus 40.4% for Grok 4.6, and Terminal-Bench 4.0 jumps from 20.3% to 38.0%. That is the kind of improvement that actually matters for agentic coding rather than just short code-generation prompts. I also like the pricing. At $2 per million input tokens and $6 per million output tokens, it is much easier to justify for daily agent workflows than some of the more expensive frontier models.

Cons

  • The downside is that the higher reasoning modes can use a lot of tokens, so I would not automatically run xhigh on every task. For quick edits or simple coding questions, a faster model can still make more sense.

Pros & Cons from Real Users

Pros

  • Meta finally opened up a genuinely frontier-level Muse model. The 1M-token context window and 42B active parameters make it strong enough for large repos, long agent sessions, multimodal work, and complex coding without feeling like a stripped-down open model. The local deployment story is also a huge deal. Being able to run something this capable on two M5 Ultra Mac Studios is impressive, especially for teams that want more control over data, infrastructure, and customization. I also like how much of the stack is open around it. Muse Spark Open works with MLX, vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, and Unsloth, and Meta is making the weights available through Hugging Face, SageMaker, Google Cloud Model Garden, and Microsoft Foundry.

Cons

  • Even though it is technically desktop-capable, needing two M5 Ultra Mac Studios for the full local experience is still a serious setup, so most developers will probably use hosted inference instead.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

SpaceXSI
Founded: 2023
United States
grok.com

Company Information

Meta
Founded: 2004
United States
research.meta.ai/blog/muse-spark-open

Alternatives

Alternatives

Grok 4.5

Grok 4.5

SpaceXSI
Grok 4.6

Grok 4.6

SpaceXSI
Laguna XS 2.1

Laguna XS 2.1

Poolside

Categories

AI Coding Models Supported
AI Models Supported
AI Vision Models Supported
Foundation Models Supported
Multimodal Models Supported

Categories

AI Coding Models Supported
AI Models Supported
AI Receptionists Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

.NET Supported
C Supported
C++ Supported
Go Supported
Grok Supported
Grok Imagine Image 2.0 Supported
Hermes Agent Supported
Java Supported
Julius AI Supported
Kotlin Supported
Microsoft Foundry Supported
Modal Not Supported
Objective-C Supported
PowerShell Supported
Python Supported
SQL Supported
Solidity Supported
SuperGrok Supported
Swift Supported
XML Supported

Integrations

.NET Not Supported
C Not Supported
C++ Not Supported
Go Not Supported
Grok Not Supported
Grok Imagine Image 2.0 Not Supported
Hermes Agent Not Supported
Java Not Supported
Julius AI Not Supported
Kotlin Not Supported
Microsoft Foundry Not Supported
Modal Supported
Objective-C Not Supported
PowerShell Not Supported
Python Not Supported
SQL Not Supported
Solidity Not Supported
SuperGrok Not Supported
Swift Not Supported
XML Not Supported
Claim Grok 4.7 and update features and information
Claim Grok 4.7 and update features and information
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information