PyTorch Day India India 2026 heads to Bengaluru
PyTorch Day India 2026 has been announced as a one-day community event focused on open-source AI and machine learning innovation in the PyTorch ecosystem. The event is scheduled for 7 February 2026 in Bengaluru, India, bringing together developers, ML engineers, researchers, and practitioners working on deep learning in production and research settings.
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Hosted by the PyTorch Foundation, co-hosted with IBM, NVIDIA and Red Hat
The event is being hosted by the PyTorch Foundation and is co-hosted with IBM, NVIDIA, and Red Hat. Organizers are positioning the program as community-driven, with a strong emphasis on sharing practical learnings, emerging techniques, and real-world implementation insights.
What to expect: talks, discussions, and poster sessions
PyTorch Day India 2026 is expected to feature a mix of:
- Technical talks covering PyTorch usage, tooling, and modern ML workflows
- Interactive discussions designed for peer learning and community exchange
- Poster sessions to showcase ideas, experiments, and applied projects
For teams building AI products, the event format suggests a balance between deep technical content and networking—useful for anyone tracking how open-source ML stacks are evolving.
Registration pricing: Early Bird and Standard
The event lists two ticket types Attendee and Academic with two pricing windows. Registration deadlines follow 11:59 PM India Standard Time on the applicable date.
Attendee pricing
- Early Bird (Jan 7–31, 2026): ₹1500
- Standard (Feb 1–7, 2026): ₹2500
Academic pricing
- Early Bird (Jan 7–31, 2026): ₹1500
- Standard (Feb 1–7, 2026): ₹1500
Academic registration typically requires proof of eligibility such as an institution ID or documentation that validates academic status.
Venue: Radisson Blu Hotel, Bengaluru Outer Ring Road.
The venue is listed as Radisson Blu Hotel, Bengaluru Outer Ring Road.
Summary
With PyTorch widely used in research and industry, PyTorch Day India acts as a focal point for open-source practitioners to compare notes on:
- production deployment patterns
- model optimization and acceleration
- training workflows and tooling
- community projects and best practices
For Indian AI teams and startups, it’s also a strong opportunity to meet peers working on similar stacks, and to see what’s trending across open-source ML engineering.
Venkat