The global AI computing race is intensifying again. On May 25, Elon Musk officially announced that xAI's latest flagship model, Grok V9-Medium, has successfully completed the training phase. As a massive foundational model with 1.5 trillion (1.5T) parameters, its scale is exactly three times that of the current v8-small version (0.5T parameters) that supports all Grok production traffic.

Key Highlights:

  • Scale Leap: From 0.5T to 1.5T parameters, the model has achieved a qualitative leap in reasoning depth and complex task handling capabilities.

  • Programming Specialization: During the supplemental training phase, xAI incorporated a vast amount of Cursor (AI programming tool) code data to significantly enhance its ability to handle complex programming tasks.

  • Timeline: The model is currently in the supervised fine-tuning (SFT) phase, and reinforcement learning (RL) will start soon. It is expected to be officially released to the public within 2 to 3 weeks.

  • Architecture Optimization: Musk revealed that the model has been deeply optimized for NVIDIA Blackwell architecture GPUs, which will significantly improve computing efficiency.

New Landscape of "Programming AI": xAI Faces Off Directly with Top Code Assistants

The release of Grok V9-Medium is particularly notable for its "programming DNA." Musk previously admitted that the existing v8-small version had obvious shortcomings in the quality, comprehensiveness, and balance of its training data, and V9-Medium is a systematic reconstruction targeting these issues.

By incorporating Cursor's code logic and practical data, xAI aims to establish a significant technical advantage within the developer ecosystem. For developers, Grok V9-Medium is not just a general chatbot but could become an "AI engineer" capable of deeply understanding complex codebases and independently completing complex programming logic.

Why Add Cursor Data?

As a mainstream AI programming assistant, Cursor represents the code calling habits, engineering thinking, and bug fixing paths of top software engineering practices. By integrating this data into "supplemental training," xAI means that Grok will skip the stage of a simple language model and directly enter the "engineering practice" stage.

This approach is seen by industry observers as xAI's "overtaking on a different track": instead of only training through general corpora, it directly learns the most authentic and direct thinking patterns of human professional engineers in programming tools.

Market Expectations: The "Benchmark" Battle of Large Models Will Be Rewritten

With Grok V9-Medium expected to launch in mid-June, competition in the AI field will enter a new phase of intense rivalry:

  • Rebuilding Performance Standards: The 1.5T parameter scale means it will directly compete with the most advanced multimodal models in logical reasoning and complex instruction following.

  • Benefits of the Blackwell Architecture: As one of the first AI large models deeply adapted to the Blackwell architecture, its performance in processing efficiency and inference cost will directly affect xAI's deployment strategy on Tesla vehicle edge devices and X platform applications.