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**ZDNET’s essential takeaways:**
– The licensing for Grok 2.5 prevents genuine open-source use.
– Elon Musk’s assertions about openness are considered misleading, falling into the category of so-called *open-washing*.
– Several other artificial intelligence projects genuinely embody openness and grant developers true freedom of use.

Technology companies frequently amplify or distort their involvement with open source, recognizing that the term resonates powerfully with both developers and investors. The promise of open access captures the imagination of enthusiastic programmers, while simultaneously stimulating financial optimism that drives shareholders to commit more capital. Yet the uncomfortable truth lurking beneath the surface is that many of these claims lack substance. They are designed more to generate excitement than to reflect actual practice.

Consider first Mark Zuckerberg’s controversial declaration that Meta’s LLaMA models were open source. This proclamation was widely criticized for stretching the definition of openness almost beyond recognition. Now, Elon Musk has stepped into the spotlight with a comparable announcement. His company, xAI, has proclaimed that Grok 2.5 — a large language model (LLM) released last year — is being provided to the public under the guise of open sourcing.

Publicly, Musk stated on X (formerly Twitter) that “the xAI Grok 2.5 model, which we regarded as our best model of last year, is now open source. Grok 3 will also be made open source in about six months.” Notably, the release includes the raw model weights, and Grok 2 can already be freely downloaded from Hugging Face, a popular platform for machine learning resources.

But one may rightly ask: why would Musk make such an announcement? Officially, xAI’s narrative emphasizes its desire to extend transparency, encourage collaborative development, and broaden the community of programmers who might test, improve, or build on Grok. This rationale mirrors the pitch of many legitimate open-source projects, where the shared ethos is that collective code enhancement benefits everyone involved.

Unofficially, however, the motivation seems far more tactical. The intention is to generate momentum around Grok by enticing developers and prospective customers to rally behind the product, thus elevating it above rival AI systems. This strategy, sometimes called *open-washing*, is the practice of invoking the open-source label without actually adhering to the standards and freedoms that true open source requires.

At the heart of the controversy lies the Grok license. Its restrictive terms radically undercut the impression that xAI has truly joined the open-source ecosystem. As the fine print makes clear: “You may not use the materials, derivatives, or outputs (including generated data) to train, create, or improve any foundational, large language, or general-purpose AI models, except for modifications or fine-tuning of Grok 2 permitted under and in accordance with the terms of this Agreement.” Such provisions radically differ from authentic open-source principles.

In other words, despite the public flourish of generosity, the restrictions mean developers cannot freely use Grok 2.5 to advance other foundational models or competing AI systems. As voices on platforms like Y Combinator have pointed out, this arrangement is not transparency in practice. Some commenters note with precision: the source code is not fully available, weight usage is hedged with constraints, and in reality what xAI has provided might more accurately be called *weights-available*, not open access.

Furthermore, when judged against the Open Source Initiative’s standards — particularly the Open Source AI Definition (OSAID) — Grok fails conspicuously. The license imposes guardrails on commercial deployment, restricting user rights through a binding Acceptable Use Policy. It explicitly bans whole categories of activity, such as utilizing Grok 2 to improve competing general-purpose AI models, thus contravening the OSI principle that precludes discrimination against any field of endeavor. The license even includes a stringent termination clause: if the user pursues certain forms of litigation, their rights to the model are revoked. None of these elements are congruent with OSI-approved licensing.

In practice, what opportunities does Grok 2.5 legitimately offer? A developer can certainly download it, run experiments, inspect its design, and tinker within boundaries set by xAI. The company presents this as an opening for educational exploration and theoretical refinement, encouraging controlled innovation within the Grok ecosystem. Yet when compared with other AI ventures — such as Mistral, Phi-2, BLOOM, or the community-driven GPT-OSS — the limitations become glaring. Those competing initiatives enable truly open exploration, providing rigorous freedom to experiment, repurpose, and even commercialize outcomes, thereby aligning with the core commitments of open-source philosophy.

One may take the Grok license at face value and engage with it as intended, using the model securely within its walled garden. But it is equally crucial not to be misled by rhetoric. If one aspires to collaborate with genuinely open-source AI, then Grok does not qualify. Its distribution is selective, its license is conditional, and the freedoms it grants are confined and controlled. Although Musk uses the language of open source, the reality is that Grok’s availability is closer to a demonstration of partial access than a true contribution to the commons.

Ultimately, developers and researchers must distinguish between marketing narratives and genuine opportunities for innovation. Grok 2.5 can certainly be a fascinating subject of study, but it should not be confused with the liberating ideals of open-source software or the ethos of unrestricted AI exploration. In short, you may experiment with Grok — but do not mistake guarded availability for actual openness. The difference is fundamental, and understanding it is essential.

Sourse: https://www.zdnet.com/article/no-grok-2-5-has-not-been-open-sourced-heres-how-you-can-tell/