# xAI Releases Grok 4.5, Its Largest Model at 1.5 Trillion Parameters

> xAI is making Grok 4.5 publicly available on July 9, and the headline is size. At roughly 1.5 trillion parameters, it is the company's largest model yet, about 50 percent bigger than Grok 4.4, and it continues xAI's habit of steady, incremental capability bumps focused on reasoning and edge-case handling rather than a dramatic redesign. The release caps a busy stretch for the company, arriving just after it wrapped up the Grok Imagine image and video generator and shipped a no-code Voice Agent Builder. It also lands under a new corporate banner: xAI now operates as SpaceXAI, following SpaceX's acquisition of the company in February 2026 and a rebranding completed in early July. A 50 percent parameter increase is a reminder that at least one lab is still betting on raw scale while much of the field pivots to efficiency and smaller specialized models. Whether that heft translates into a real quality edge over rivals, or just a bigger inference bill, is the question the benchmarks will have to answer once it is in users' hands.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: xAI · Published Wednesday, July 8, 2026_

## Wortins' read

xAI is making Grok 4.5 publicly available on July 9, and the headline is size. At roughly 1.5 trillion parameters, it is the company's largest model yet, about 50 percent bigger than Grok 4.4, and it continues xAI's habit of steady, incremental capability bumps focused on reasoning and edge-case handling rather than a dramatic redesign. The release caps a busy stretch for the company, arriving just after it wrapped up the Grok Imagine image and video generator and shipped a no-code Voice Agent Builder. It also lands under a new corporate banner: xAI now operates as SpaceXAI, following SpaceX's acquisition of the company in February 2026 and a rebranding completed in early July. A 50 percent parameter increase is a reminder that at least one lab is still betting on raw scale while much of the field pivots to efficiency and smaller specialized models. Whether that heft translates into a real quality edge over rivals, or just a bigger inference bill, is the question the benchmarks will have to answer once it is in users' hands.

## Source

[Read the full story at xAI](https://x.ai/news)

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