📂 Assistant Code 👁 2.6k views 🕐 May 21, 2026

Grok-1

Grok-1 is an open-source AI model designed for researchers and developers, it.

Grok-1 is an open-source AI model designed for researchers and developers, it is currently designed with 48 attention heads for queries and 8 for keys/values. The model supports activation sharding and 8-bit quantization, making it a unique tool for those looking to work with large models. The implementation of the MoE layer in this repository is not efficient but was chosen to avoid the need for custom kernels to validate the correctness of the model. Grok-1 is best suited for those who need a highly customizable AI model with specific architecture requirements. The model's open-source nature and availability on GitHub make it an excellent choice for researchers and developers who want to contribute to its development or use it as a starting point for their projects.

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Features
Attention Heads
48 for queries, 8 for keys/values, allowing for complex input processing
Experts Utilization
2 experts used per token, enabling efficient processing of large datasets
Supports activation sharding and 8-bit quantization, reducing computational requirements
Architecture
Mixture of 8 Experts (MoE), providing a unique approach to AI model design
Verdict
Best forTeams doing Assistant Code work who need consistent output without a steep learning curve.
Skip ifYou only need this once or twice; the subscription cost won't pay off for occasional use.
Highly customizable AI model with specific architecture requirements
Open-source nature allows for community contributions and transparency
Supports activation sharding and 8-bit quantization, making it suitable for large-scale applications
The implementation of the MoE layer is not efficient, which may impact performance
Requires a machine with enough GPU memory to test the model with the example code
Alternatives
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Frequently Asked Questions
Grok-1 is an open-source AI model designed for researchers and developers, it supports activation sharding and 8-bit quantization.
You can download Grok-1 using a torrent client and the provided magnet link, or directly using HuggingFace Hub.
Grok-1 requires a machine with enough GPU memory to test the model with the example code, due to its large size of 314B parameters.
The code and associated Grok-1 weights are licensed under the Apache 2.0 license, which allows for commercial use.
Grok-1's unique architecture and customization options make it a distinct choice, but its inefficient MoE layer implementation may impact performance compared to other models.
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