Grok's next generation is nearly ready to ship. On May 25, SpaceXAI chief Elon Musk announced that Grok foundation model V9-Medium — a 1.5 trillion-parameter model three times larger than the version currently handling all Grok production traffic — has completed training, with evaluation results described as positive. Supervised fine-tuning is underway; reinforcement learning was set to begin within days of the announcement; and a public release is expected approximately two to three weeks from that date, placing it in mid-June 2026. For developers who rely on AI coding tools, that release window matters: V9-Medium was explicitly trained on Cursor data — real-world developer workflows from one of the most widely used AI code editors — and Musk has called it a major step forward specifically for complex programming tasks.
The current model in production is the v8-small, running on roughly 500 billion parameters. Musk has described it candidly as "just 0.5T" and acknowledged it is missing important training data. V9-Medium, at 1.5 trillion parameters, is the correction — and the pipeline behind it points toward something significantly larger still.
Cursor Training Data: Why Source Matters
The most consequential technical detail in Musk's announcement is not the parameter count. It is the training data. Cursor, the AI-augmented code editor used by developers at companies including OpenAI, Stripe, and Perplexity, became the source of supplementary training data for V9-Medium, with Musk noting that more Cursor data will continue to be added. That decision matters because it means V9-Medium was not trained only on public GitHub repositories — the standard corpus for most coding models — but on actual developer workflows, including how real engineers debug, refactor, and extend production codebases.
SpaceXAI reached an agreement with Anysphere, Cursor's developer, giving SpaceX the right to acquire the company for $60 billion later in 2026, or to pay $10 billion for collaborative work. That deal — announced in April 2026 — now has a clearer technical rationale: the Cursor data pipeline feeding into V9-Medium is part of a deeper integration plan, not a one-off training decision.
What V9-Medium Is Competing Against
The model enters a market where Grok currently holds approximately 6% enterprise AI adoption, compared with 55% for OpenAI, 47% for Anthropic, and 39% for Google, according to Enterprise Technology Research data from March 2026. On coding benchmarks, the gap is real: Claude Opus 4.7 leads SWE-bench Verified at 87.6%, while Grok 4 — the product brand currently layered above the v8-small foundation — reaches 75% on the same benchmark. Whether tripling the parameter count and incorporating Cursor workflow data closes that gap is precisely what the mid-June release will test.
Analysts have consistently noted that raw parameter scale does not produce proportionally better performance. Mixture-of-Experts architectures, of the kind used by DeepSeek, can match or outperform dense models at a fraction of total parameter activation. The quality of training data and the precision of the post-training alignment phase matter at least as much as size. V9-Medium's Cursor data strategy reflects an awareness of that constraint.