Grok 4.6 gets Aug. 7 launch date, Grok 4.7 follows

Elon Musk has set an early August target for Grok 4.6 and disclosed plans for a larger Grok 4.7 model as SpaceXAI steps up its competition with OpenAI, Anthropic, and China's Moonshot AI.

Grok 4.6 targets an Aug. 7 release

Musk disclosed the timeline in a July 28 post on X, saying Grok 4.6 would be released "around August 7." He described it as a 1.5 trillion-parameter model with stronger supervised fine-tuning and reinforcement learning.

Supervised fine-tuning trains a model on selected examples to improve the quality of its responses. Reinforcement learning uses feedback and reward signals to refine how a model handles tasks and follows instructions.

Musk also said Grok 4.7 would follow "a few weeks later" as a 2.1 trillion-parameter model. However, he did not provide an exact launch date or disclose pricing and availability details for either release.

Both dates remain targets rather than confirmed release appointments. Model development schedules can change during training, testing, and deployment.

Grok 4.5 sets the baseline for the upgrades

SpaceXAI introduced Grok 4.5 earlier in July as a model designed for coding, agent-based tasks, and knowledge work. Musk announced the next two models in response to an assessment from Vercel CEO Guillermo Rauch, who described Grok 4.5 as the best-performing cybersecurity model relative to its price in Vercel's latest tests.

According to Rauch's post, Grok 4.5 was 10 times cheaper than OpenAI's GPT-5.6 Sol, 5.7 times cheaper than Anthropic's Opus 5, and 2.2 times cheaper than Moonshot's Kimi K3 while delivering performance close to Kimi.

US AI firms face pressure from China's Kimi K3

Grok's planned upgrades arrive as Chinese developers narrow the gap with leading US AI companies. Moonshot AI released the full weights for Kimi K3 on July 27, allowing developers to download, modify, and operate the model on their own infrastructure.

SpaceXAI, OpenAI, and Anthropic are also competing on coding, cybersecurity, reasoning, and the cost required to complete each task. Grok 4.7's larger architecture may improve its capabilities, but Musk acknowledged that it would be slower to serve than Grok 4.6.

Parameter counts alone do not determine model quality. Training data, architecture, post-training methods, inference systems, and token efficiency can all affect performance.

US AI firms split over federal oversight

OpenAI and Anthropic have already agreed to provide US officials with early access to unreleased frontier models for safety testing. Those agreements formed the basis for a broader voluntary federal review framework that now covers other major developers, including SpaceXAI, Google DeepMind, and Microsoft.

However, the industry remains divided over how Washington should handle open-weight models. Nvidia, Microsoft, Meta, OpenAI, Palantir, and other organizations warned US policymakers against broad restrictions in a July 24 open letter. They argued that open models support competition, lower deployment costs, and allow developers to run and modify AI systems on their own infrastructure.

The debate has intensified following Moonshot AI's release of the 2.8 trillion-parameter Kimi K3. Trump administration officials have accused Moonshot of using outputs from Anthropic's Fable model to train Kimi K3 through large-scale distillation. The dispute has nevertheless placed Kimi K3 at the center of a wider policy fight over whether Washington should target specific security and intellectual-property risks or restrict access to Chinese open-weight models more broadly. Grok 4.6 and Grok 4.7 will enter that market as US developers face pressure to improve performance while meeting emerging federal safety expectations.

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