# xAI releases Grok 4.5: 1.5 trillion parameter MoE model trained on Cursor data

> xAI's Grok 4.5 is a 1.5-trillion-parameter Mixture-of-Experts model with a 500,000-token context window, and its headline detail is how it was trained. xAI says the model learned alongside the Cursor coding environment, using real IDE session data to shape its post-training for coding and agentic work rather than relying on synthetic benchmarks alone. The payoff, per xAI, is efficiency. Grok 4.5 posts an 83.3% score on Terminal Bench 2.1 while using roughly a quarter fewer output tokens than Claude Opus 4.8 to get there, which matters because output tokens are where inference costs pile up. It supports low, medium, and high reasoning-effort levels, with high as the default, and lands fourth on the Artificial Analysis Intelligence Index. None of that makes Grok the outright leader, and it sits tied with rivals on several coding measures. But training a frontier model directly against a working developer tool is a genuinely different approach, and the token-efficiency angle is the kind of practical edge that enterprises actually pay attention to.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: xAI · Published Thursday, July 23, 2026_

## Wortins' read

xAI's Grok 4.5 is a 1.5-trillion-parameter Mixture-of-Experts model with a 500,000-token context window, and its headline detail is how it was trained. xAI says the model learned alongside the Cursor coding environment, using real IDE session data to shape its post-training for coding and agentic work rather than relying on synthetic benchmarks alone. The payoff, per xAI, is efficiency. Grok 4.5 posts an 83.3% score on Terminal Bench 2.1 while using roughly a quarter fewer output tokens than Claude Opus 4.8 to get there, which matters because output tokens are where inference costs pile up. It supports low, medium, and high reasoning-effort levels, with high as the default, and lands fourth on the Artificial Analysis Intelligence Index. None of that makes Grok the outright leader, and it sits tied with rivals on several coding measures. But training a frontier model directly against a working developer tool is a genuinely different approach, and the token-efficiency angle is the kind of practical edge that enterprises actually pay attention to.

## Source

[Read the full story at xAI](https://explainx.ai/blog/grok-4-5-public-launch-spacexai-july-2026)

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