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Meta’s “personal use” defense did not end the case. In October 2025, Meta argued that alleged BitTorrent downloads linked to its network were sporadic activity by employees, contractors, visitors, or others—not a company-directed effort to collect adult films for AI training. On June 11, 2026, Judge Eumi K. Lee denied Meta’s motion to dismiss, allowing the copyright lawsuit to continue.
That ruling does not prove that Meta trained an AI model on the films, that executives ordered the downloads, or that Meta is liable. It means the plaintiffs pleaded enough facts for their claims to proceed into litigation.
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What the lawsuit alleges
Strike 3 Holdings and Counterlife Media sued Meta Platforms in the U.S. District Court for the Northern District of California on July 23, 2025. The case is 5:25-cv-06213-EKL, before Judge Eumi K. Lee.
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Those are allegations, not established facts. The public court ruling did not find that Meta used the films in an AI-training dataset.
What Meta denied
In its October 27, 2025 motion to dismiss, Meta rejected the theory that the downloads were part of a corporate AI-data operation. Its arguments included:
- The alleged activity began in 2018, before the generative-video and multimodal-model work identified by the plaintiffs, which Meta associated with roughly 2022 onward.
- The activity was intermittent and relatively limited when considered per corporate IP address.
- Multiple, disparate IP addresses were more consistent with individuals using company networks than with one centrally controlled system.
- There was no pleaded evidence that the films were actually used to train a particular AI model.
- Employees, contractors, visitors, or other users could have downloaded the material for private purposes.
- Meta’s AI policies prohibit generating or facilitating adult content, which Meta said made an adult-content training project less plausible.
“Personal use” is therefore Meta’s litigation position about who may have caused the activity and why. It is not a verified explanation for every download.
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Why BitTorrent matters legally
BitTorrent is a peer-to-peer protocol. A file is divided into pieces, and a user typically receives pieces from multiple peers while potentially uploading pieces to others. The exact behavior depends on the client and configuration, but the alleged activity can involve more than simply watching a stream.
That distinction matters because copyright owners have separate exclusive rights involving reproduction and distribution. The plaintiffs argue that downloading and sharing pieces through a BitTorrent swarm could implicate both. “Personal use” does not automatically eliminate a copyright claim, particularly if unauthorized copying or distribution occurred.
Why the judge allowed the case to continue
At the motion-to-dismiss stage, a court generally assumes well-pleaded factual allegations are true and asks whether they plausibly support a legal claim. It does not decide which side’s evidence will ultimately prevail.
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In the June 11, 2026 order, Judge Lee concluded that the plaintiffs had plausibly alleged copyright infringement and sufficient involvement by Meta to move beyond the pleadings.
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The court also rejected the idea that the plaintiffs necessarily had to identify a specific Meta AI model trained on each film. The alleged unauthorized copying or distribution through BitTorrent could itself support a direct-infringement claim if the plaintiffs can later prove the necessary facts.
The judge pointed to allegations involving repeated activity, similar or coordinated filenames, changes in infrastructure, and tools allegedly tailored to BitTorrent use. Those allegations did not prove an automated Meta operation, but they were enough to make the plaintiffs’ theory plausible at this stage.
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What the ruling did not decide
The decision did not establish that:
- Meta trained Movie Gen or another model on the adult films;
- Meta created an undisclosed adult-content AI model;
- Meta executives directed employees to download the material;
- every Meta-linked IP address was operated by Meta rather than an individual or third party;
- the downloads were authorized by Meta;
- Meta is ultimately liable for infringement; or
- fair use protects the alleged conduct.
The AI-training theory may remain important to questions of motive, damages, discovery, and the plaintiffs’ broader claims. But the court indicated that the direct copyright claim did not depend entirely on proving that the films entered model-training data.
The competing explanations
| Meta’s position | Plaintiffs’ position |
|---|---|
| The activity was scattered, intermittent, and relatively small per IP address. | The timing, filenames, infrastructure changes, and tools showed coordination. |
| The alleged torrenting began before Meta’s cited generative-AI work. | The activity was part of a broader effort to acquire copyrighted material for AI. |
| Employees, contractors, visitors, or other users could have acted privately. | Corporate networks, servers, accounts, cloud infrastructure, and related resources were allegedly used to facilitate the operation. |
| No evidence showed that the films were used to train a model. | The alleged copying and distribution were independently actionable, even if training use remains unproven. |
A corporate IP address alone does not establish corporate authorization. It can identify a network or infrastructure path without proving who operated the device or whether the company directed the conduct. That attribution question is likely to be important as the case develops.
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Damages claims are not an expected judgment
Early reporting described potential damages claims exceeding $350 million, while later summaries discussed larger economic stakes in the broader AI context. Those figures reflect positions reported in pleadings or coverage—not an award, valuation, or prediction of the final result.
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Any eventual damages would depend on issues such as the number of works involved, whether infringement is proven, whether conduct was willful, and whether the plaintiffs pursue statutory or actual damages. None of those questions was resolved by the dismissal ruling.
Other reported developments
A February 2026 discovery-related filing reported the plaintiffs’ claim that a Meta employee had recently deleted more than 9 terabytes of torrented files. That was an allegation in a discovery dispute, not a judicial finding that the deletion was unlawful or intended to destroy evidence.
July 2026 reporting about Meta’s answer to an amended complaint said the company acknowledged that a key IP address was associated with a person who became a Meta data engineer in April 2025 and left in May 2026, while continuing to deny the plaintiffs’ claims. That development should be read alongside the operative docket filings rather than as proof that the person or Meta directed the alleged activity.
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- 2018 onward: The plaintiffs allege that Meta-linked BitTorrent activity involving their films began during this period.
- Around 2022: Meta identified this period as the beginning of the multimodal and generative-video work cited by the plaintiffs.
- July 23, 2025: Strike 3 and Counterlife filed the lawsuit.
- October 27, 2025: Meta filed its motion to dismiss and argued that the activity was more consistent with personal use than AI training.
- February 11, 2026: The court held a hearing on the motion.
- June 11, 2026: Judge Lee denied dismissal, allowing the lawsuit to proceed.
The current procedural takeaway is simple: the case survived an early attempt to end it. The next stages can address evidence, attribution, authorization, alleged copying and distribution, the role of AI training, and damages.
Why this matters beyond Meta
The dispute illustrates an important distinction in AI-copyright litigation. A company may face questions about how copyrighted material was acquired even when a plaintiff cannot yet prove that the material was used to train a named model. It also shows why network evidence, user identity, corporate authorization, file handling, and data provenance can matter separately.
The ruling does not resolve whether AI training on copyrighted material is fair use or establish that AI companies are liable whenever copyrighted files appear on their networks. It is a procedural decision allowing this particular set of allegations to be tested through litigation.
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