The landscape of artificial intelligence voice assistants is rapidly evolving, and Apple is intensifying its efforts to remain at the forefront. According to a recent Bloomberg report, Apple has been internally testing advanced Large Language Models (LLMs) for Siri—models that, in some benchmarks, approach or even match the capabilities of industry leaders such as OpenAI's ChatGPT.
Internal AI Models: Significant Progress
While Apple recently introduced Apple Intelligence, a suite of AI-powered features focused on privacy and on-device processing, sources indicate that much more powerful LLMs are in development within the company. The report details that Apple’s research teams are currently experimenting with models spanning a range of complexities, including LLMs with 3 billion, 7 billion, 33 billion, and up to 150 billion parameters. For context, models at the top end of this range are similar in size to those that underpin today's leading AI chatbots.
Apple has reportedly used these models to test next-generation Siri prototypes. Results suggest that, in controlled settings, the upgraded Siri can reach levels of conversational accuracy and problem-solving on par with ChatGPT. However, the development process has highlighted ongoing challenges—most notably, the issue of hallucinations, where the AI produces confident but inaccurate statements. According to Bloomberg, Apple executives remain concerned about releasing a voice assistant that could deliver unreliable or misleading responses, particularly given the company's history of emphasizing high reliability and user privacy.
Strategic Considerations for Deployment
Decisions about when and how to deliver these enhanced Siri capabilities are reportedly a matter of internal debate at Apple. Some executives advocate for proceeding as soon as technical milestones are reached, leveraging advancements to improve Siri’s competitiveness. Others urge caution, citing potential reputational risks if the user-facing version does not meet Apple's high standards for reliability and privacy.
Apple’s approach to AI deployment has been distinct from some competitors. While companies like Microsoft and Google have quickly integrated advanced generative AI into their products, Apple has prioritized models that run on-device or in tightly controlled server environments. This design decision aligns with Apple’s stated commitment to user privacy, as much data processing happens locally rather than in the cloud. The ongoing internal testing of higher-parameter LLMs appears to be a measured step towards expanding Siri’s intelligence without compromising Apple's established privacy framework.
AI Performance and Reliability: Industry Context
Industry analysts suggest that achieving ChatGPT-level conversational ability requires both large models and robust guardrails against hallucinations. While launching a more capable Siri could significantly close the AI assistant gap, reliability remains a core concern. Apple's preference for on-device AI, while furthering privacy, presents technical limitations due to device hardware constraints. The company’s exploration of larger models likely includes solutions such as hybrid on-device/cloud inference and new AI safety techniques.
Recent research publications from Apple indicate ongoing progress on both efficiency and reliability within LLMs. The company has consistently published papers detailing methods for reducing hallucinations, increasing factual accuracy, and improving computational efficiency. This research-driven approach provides insight into why Apple may be pursuing a cautious timeline for public deployment.
Implications for Apple Users and Developers
If Apple moves forward with releasing a next-generation Siri powered by large-scale LLMs, several outcomes are possible:
- User Experience Enhancements: Users could see more natural, responsive, and context-aware interactions across iPhone, iPad, and Mac. Information queries, app commands, and multi-turn conversations could become more dynamic and precise.
- Developer Opportunities: A more advanced Siri may allow third-party developers to build deeper integrations using SiriKit and related APIs, enabling broader use cases in productivity, entertainment, and accessibility.
- Privacy and Reliability Trade-Offs: As Apple explores cloud-based inference for larger models, transparent communication regarding data usage and privacy safeguards will likely remain a core component of any rollout. Balancing cutting-edge AI features against potential risks of misinformation will be a central challenge.
- Competitive Positioning: Achieving ChatGPT-level functionality in Siri could mitigate the perception that Apple is lagging in AI and further differentiate Apple devices, especially for users who prioritize both intelligence and privacy.
Looking Ahead: Apple's AI Roadmap
Apple has not made any official announcements about public availability of these internal models. However, the ongoing pace of research, the scale of internal testing, and executive-level focus on AI as a critical differentiator point toward a significant Siri upgrade on the horizon. The company’s upcoming Worldwide Developers Conference (WWDC) or fall hardware events could be key moments to watch for future AI announcements.
Developments around Siri and Apple Intelligence remain closely watched by both industry observers and Apple’s user base. The company’s next steps could help define user expectations for trustworthy, privacy-preserving AI experiences on consumer devices.