• Hackathon Radar
Hackathons
  • Browse
  • Judge Opportunities
  • Sponsors
  • Organizers
  • Map
  • Discover
Personal
  • Custom Views
  • Passport
  • Favorites
Explore
  • Stats
  • State of Hackathons
  • Changelog
  • Settings

Qualcomm x Meta ExecuTorch Hackathon

lablabHosted on Lablab.ai

Fetched 18 days ago

Saturday, June 27, 2026

to Sunday, June 28, 2026

•

1 day long

Artificial Intelligence

Event Type

hybrid

10

Participants

USD23

Prize Pool

0

Est. Projects

On-site Only Hackathon | June 27–28, 2026 | San Francisco, CA This is an in-person hackathon in San Francisco for selected participants. Capacity is limited to 150 people, teams must include 3–5 members, and there is no online or hybrid participation. Build and optimize real-time AI applications that run directly on Snapdragon-powered mobile devices using ExecuTorch. On-site Venue (May 30–31): The Web Data Loft 625 2nd St, San Francisco, CA Build on Samsung Galaxy S25 Ultra devices powered by Snapdragon Learn from Qualcomm and Meta experts through workshops, mentorship, and hands-on support. Prizes include Meta Quest 3 headsets, Ray-Ban Meta AI Glasses, and post-event project support. Apply now to build the future of on-device AI with ExecuTorch and Snapdragon. Once pre-approved, you will receive further instructions on how to complete the acceptance process. Application deadline: June 15, 2026.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct