TimeNet has announced an online hackathon focused on Time-Series Language Models (TSLMs), challenging developers to build practical AI solutions for forecasting, classification, and anomaly detection. The inaugural round closes on November 22, 2026, at 11:59 p.m. PST, with judging scheduled for the following Monday. This event targets the intersection of infrastructure and applied AI, requiring participants to onboard datasets into the TimeNet format and fine-tune models like OpenTSLM.

Compute Credits and Cloud Prizes

The competition offers tangible infrastructure resources to lower the barrier for model training. Teams can apply for Nebius vouchers worth $100 or $500, allocated on a rolling basis based on project potential and availability. For the winning teams, TimeNet is offering starting prizes of $25,000 in credits from both AWS and Google Cloud. This structure suggests a serious push to get TSLMs into production environments rather than just staying in academic benchmarks.

Submission Requirements and Workflow

Participation requires a specific technical workflow: teams of 2โ€“4 people must submit a Pull Request adding their dataset to TimeNet, alongside a project pitch or demo. The judging criteria explicitly include the clarity and traction of public posts on X and LinkedIn, meaning social engineering is now a formal part of the technical evaluation. Participants must also include screenshots of available metrics to validate their results, ensuring that the 'demo' aspect isn't just vaporware.

Key Takeaways

  • Round 1 submissions close November 22, 2026, at 11:59 p.m. PST (UTCโˆ’8).
  • Teams can receive $100โ€“$500 in Nebius compute credits via rolling applications.
  • Winners receive starting prizes of $25,000 in AWS and Google Cloud credits.
  • Projects must be judged on technical execution, data quality, and social media engagement.
  • OpenTSLM is cited as a primary example model for fine-tuning tasks.

The Bottom Line

This isn't just a coding contest; it's a distribution strategy for TimeNet's data format and a testbed for TSLMs. If you have a niche time-series problem, the cloud credits are a valid excuse to finally ship it.