Elon Musk’s xAI Holdings Corp. has released grok-code-fast-1, a dedicated agentic coding artificial intelligence model that is extremely speedy and designed to strike a “compelling balance between performance and cost.”
In a market that is quickly becoming cluttered with models offering coding capabilities, xAI said Thursday it built the model from the ground up and built it with a brand-new architecture fit for task.
“Throughout the training process, we collaborated closely with our launch partners to refine and sharpen the model’s behavior inside their agentic platforms,” the company said. “Grok-code-fast-1 has mastered the use of common tools like grep, terminal, and file editing, and thus should feel right at home in your favorite IDE.”
At launch, the new model will be available for free for a limited time within popular AI-enabled coding platforms, including GitHub Copilot, Cursor, Cline, Roo Code, Kilo Cline, Opencode and Windsurf.
The model supports function calling, structured outputs and reasoning with a 256,000-token context window. This window size enables the model to recall the equivalent of hundreds of pages of text or code simultaneously, allowing it to efficiently review large portions of codebases while working.
As for speed, according to xAI’s own benchmarks, the new model can execute at about 160 tokens per second. Compared with other popular models on the market on the same xAI released benchmarks, OpenAI’s GPT-5 averages about 50.1 tokens per second, Gemini 2.5 Pro hit about 92.4 and Claude 4 Sonnet reached 78.7.
“In early testing, Grok Code Fast has shown both its speed and quality in agentic coding tasks,” said Mario Rodriguez, chief product officer of GitHub Inc. “Empowering developers with powerful tools is a core part of our mission at GitHub Copilot, and this is a compelling new option for our developers.”
Last week, xAI stealthily released grok-code-fast-1 under the codename sonic. During this phase, the research team monitored community channels and adjusted the model according to feedback.
The company said on a full subset of SWE-Bench-Verified, a human-validated evaluation of the AI model’s ability to solve real-world software engineering problems, the model received a 70.8% using an internal system. In comparison, GPT-5 received a 74.9% (with thinking) and Claude Sonnet 4 achieved 72.7%.
The model was designed to be flexible across various coding languages, with high proficiency in TypeScript, Python, Java, Rust, C++ and Go.
The model is available through the xAI application programming interface service for developers, priced at 20 cents per 1 million input tokens, $1.50 per 1 million output tokens, and two cents per 1 million cached input tokens.
Given that xAI will be competing against multiple other models on the market that provide coding capabilities, the company said it intends to deliver consistent updates and improvements on the order of days rather than weeks.
The company teased a new variant that supports multimodal inputs, parallel tool calling and extended context as the first upcoming release.
Images: xAI
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