Grok Code Fast
Parameters
314B
Context Length
128K
Modality
Text
Architecture
Dense
License
Proprietary
Release Date
1 Jun 2025
Knowledge Cutoff
Jan 2025
Evaluation Benchmarks
Rank
#153
| Benchmark | Score | Rank |
|---|---|---|
Web Development | 1164 | 64 |
Rankings
Overall Rank
#153
Coding Rank
#88
About Grok Code Fast
Grok Code Fast is a specialized large language model developed by xAI, engineered specifically to support high-velocity agentic coding workflows. Built from the ground up with a custom architecture, the model is pre-trained on a massive corpus of programming-related data and fine-tuned using high-quality post-training datasets derived from real-world pull requests and practical software engineering tasks. This specialization allows the model to maintain a high degree of proficiency in popular languages such as TypeScript, Python, Java, Rust, C++, and Go, while remaining optimized for the low-latency demands of real-time development environments.
Technically, the model utilizes a sparse Mixture-of-Experts (MoE) architecture designed to balance computational efficiency with high-capacity reasoning. This structural choice enables the model to process complex instructions and manage multi-step tool interactions without the latency penalties typically associated with dense models of similar scale. A defining characteristic of Grok Code Fast is its deep integration with developer tools; it is specifically trained to execute terminal operations, perform repository-wide file searches using utilities like grep, and carry out precise code refactors. The model also incorporates advanced prompt caching techniques, which significantly reduce response times for repetitive context-heavy queries common in IDE-based interactions.
In practical application, Grok Code Fast is optimized for autonomous and semi-autonomous tasks such as project scaffolding, codebase exploration, and surgical bug fixing. It features an expansive 256,000-token context window, providing the necessary memory for the model to ingest and reason over substantial portions of a repository simultaneously. By prioritizing throughput and tool-calling reliability, the model serves as a responsive backend for modern AI-driven coding assistants and automated agents that require a tight feedback loop between reasoning and code execution.
Technical Specifications
Detailed architecture specifications are limited for proprietary models.
Resources
About Grok
xAI's conversational AI models with real-time knowledge access and strong performance across reasoning, coding, and language tasks. Features extended context windows, fast inference variants, and specialized coding versions. Known for direct communication style and integration with X platform. Includes reasoning variants and optimized versions for different latency requirements.