Grok Code Fast 1

Grok Code Fast 1

Model family: Grok

Announced on August 28, 2025, Grok Code Fast 1 is a speedy, economical reasoning model purpose-built for agentic coding. It “thinks before responding,” supports function calling and structured outputs, and provides a 256,000-token context window for large codebases. Official pricing is $0.20 per million input tokens, $1.50/M output, and $0.02/M cached input; live search isn’t supported. Typical rate limits are 480 requests/minute and 2M tokens/minute. xAI highlights fast tool-use loops and visible “thinking trace,” and notes strong performance on everyday coding tasks across TypeScript, Python, Java, Rust, C++, and Go. It’s generally available via the xAI API, with limited-time free access through partners like GitHub Copilot, Cursor, and Cline.

Overview

Grok Code Fast 1 is xAI’s low-cost, high-speed coding model for “agentic” workflows. It offers a 256K-token context, function calling, structured outputs, and pricing at $0.20/M input, $1.50/M output ($0.02/M cached). Available via the xAI API

About xAI

xAI is an artificial intelligence startup founded by Elon Musk, aiming to understand the universe.

Industry: Artificial Intelligence

Company Size: 1200

Location: Palo Alto, California, US

Website: x.ai

View Company Profile

Benchmark scores

How Grok Code Fast 1 ranks on tracked AI benchmarks. Click any benchmark to see its full leaderboard.

SWE-bench Verified

Coding

70.8%

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Tools using Grok Code Fast 1

Grok 4.5

Conversational AI for understanding the universe.

Productivity

Open

Grok — v4.5

Handles difficult long-running tasks more effectively by investigating problems, using tools, recovering from mistakes, and verifying results in realistic environments. Extends beyond software engineering into data science, finance, legal work, and other computer-based knowledge tasks with a broader training mix. Improves agent-style computer work through training on large volumes of codebase interactions and developer-agent behavior with software tools. Gains stronger robustness on hard problems through reinforcement learning environments designed specifically to remain challenging even for frontier systems. Offers a separate fast variant, indicating a higher-speed option alongside the main weight class for lower-latency workflows.

5

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