November 7–8 · San Francisco

Vals AI Hackathon

For one weekend, benchmaxxing is the point. Post-train a small model to the top of three Vals benchmarks, or build a new eval that frontier models still fail.

November 7–8, 2026 The Mission, San Francisco
Apply on Luma
Vals Hacks, San Francisco, November 7–8, 2026
24
Hours, noon to noon
150
Spots
1–4
People per team
Free
To attend

About

Train a model or build an eval.

Use the same infrastructure we use to benchmark model releases, including Valkyrie, our open-source harness for agentic evals. Top projects get featured on vals.ai.

Tracks

01

Post-Training

Post-train a small model and score it on three Vals benchmarks, using compute from our sponsors.

Ranked on a live leaderboard. Prizes for 1st, 2nd and 3rd.

02

Build Your Own Eval

Build a benchmark on Valkyrie for a task frontier models still get wrong. We cover model and compute costs.

Judged on demos. Prizes for 1st, 2nd and 3rd.

Schedule

Doors open in

-- Days
-- Hrs
-- Min
-- Sec

Sat, Nov 7 · 12 PM PT

  1. Sat 12 PM Check-in and snacks
  2. Sat 1 PM Opening remarks
  3. Sat 2 PM Hacking begins
  4. Sat 5 PM Cybersecurity CTF (optional side quest)
  5. Sat 7 PM Dinner and speakers
  6. Sat 10 PM Dessert and show-and-tell
  7. Sun 9 AM Breakfast
  8. Sun 10 AM Submissions close, demos and judging
  9. Sun 12 PM Winners announced

FAQ

Who can apply?

Anyone can apply, but we give preference to applicants with technical experience.

Do I need a team?

No, but we recommend one. Apply with a team of up to four, or apply solo and we'll match you with a team on-site.

Are there prizes?

Yes. Prizes for 1st, 2nd and 3rd place in each track.

What do I get access to?
  • Post-Training: Sponsor compute and credits, plus automatic scoring on all three benchmarks.
  • Build Your Own Eval: Valkyrie, our open-source eval harness. We cover model and compute costs.
Is food provided?

Yes. Lunch, dinner, breakfast and snacks. Note any dietary restrictions when you apply.

Interested in sponsoring? Email rayan@vals.ai or miyuki@vals.ai.