Boston vs Seoul

Boston has more capital; Seoul has the stronger notable-model count. This page picks the chart shape from the data instead of forcing every comparison into the same visual.

MODEL FLIP

00 — Screenshot hook

Boston has the money. Seoul has the notable models.

Boston

$2.0B

Seoul

$1.7B

Boston

Seoul

9 to 1 tracked notable AI models; 1.2× funding gap. Tracked notable-model denominator only.

TRACKED AI-NATIVE FUNDING VS TRACKED NOTABLE MODELS NO ORG-BENCH OR COMPUTE CHIPS IN THIS SCREENSHOT

01 — Share of world

Boston 1/100 Seoul 1/100 rest of world 98/100

Together = 2% of all AI funding tracked worldwide.

Boston: 0.50% of world · Seoul: 0.42% of world

🇺🇸 Boston

1/100

$2.0B · #8 of 12

🇰🇷 Seoul

1/100

$1.7B · #9 of 12

SRC: epoch · forbes · cbi · manual-gaps 1 SQUARE = 1% OF WORLD AI FUNDING

01.5 — Why this comparison matters

The useful read hub vs hub

┌─ generated from funding, org, model, compute, and overlap signals ─────────────────────────────── ┐

Boston has more capital; Seoul has the stronger notable-model count.

Boston's biggest carrier is OpenEvidence: $700M (34.6% of tracked side funding). Seoul's biggest carrier is Rebellions: $850M (50.1% of tracked side funding).

The org treemap is shown because both sides have enough funded orgs for area to mean something.

Funding is HQ-based and limited to AI-native orgs. Compute is counted by datacenter location, so it can disagree with headquarters funding.

NOINDEX: KEEP USEFUL, AVOID THIN SERP SPAM CANONICAL /vs/boston-vs-seoul/

note — Boston runs 1.2× more AI capital than Seoul. Whether that translates to frontier compute is what the next chart shows.

— ai-race-map · methodology @ /m

03 — Org capital concentration

Boston's top 3 absorb 79% of tracked funding

Seoul's top 3 hold 81% of tracked funding.

org upset

🇺🇸 Boston 8 orgs · $2.0B

top 1 35%

top 3 79%