AI-RACE-MAP.COM
← world map
/vs/in-vs-kr/  ·  updated 2026-05-08
compare

India vs South Korea

India leads on AI funding; South Korea leads on operational compute. This page picks the chart shape from the data instead of forcing every comparison into the same visual.

COMPUTE FLIP
00 — Planned-campus dependency
One unbuilt campus would be 88.7% of India's current-plus-next AI data-center MW.
India
88.7% planned
South Korea
11.7% planned
AdaniConneX-Google Visakhapatnam AI Data Center Campus: 1.0 GW SK Telecom-AWS Ulsan AI Data Center: 41 MW
Denominator is operational MW plus the single largest planned campus, not total future pipeline. India: 127 MW live + 1.0 GW planned.
POWER_MW FIELD · OPERATIONAL BASE PLUS LARGEST PLANNED SITE PLANNED/UNBUILT STATUS KEPT IN THE MAIN FACT
00 — Screenshot hook
India has the money. South Korea has the notable models.
India
$2.3B
South Korea
$1.7B
India
0
0
South Korea
9
9 to 0 tracked notable AI models; 1.4× 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
India 1/100 South Korea 1/100 rest of world 98/100
Together = 2% of all AI funding tracked worldwide.
India: 0.56% of world · South Korea: 0.42% of world
🇮🇳 India
1/100
$2.3B · #7 of 49
🇰🇷 South Korea
1/100
$1.7B · #8 of 49
SRC: epoch · forbes · cbi · manual-gaps 1 SQUARE = 1% OF WORLD AI FUNDING
01.5 — Why this comparison matters

The useful read country vs country

┌─ generated from funding, org, model, compute, and overlap signals ─────────────────────────────── ┐
India leads on AI funding; South Korea leads on operational compute.
India's biggest carrier is Yotta Data Services: $2.0B (87.0% of tracked side funding). South Korea'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.
INDEXABLE TOP-100 PAIR CANONICAL /vs/in-vs-kr/
02 — Metric board
🇮🇳 India
#7 of 49 · country
━━ vs ━━
South Korea 🇰🇷
#8 of 49 · country
NOTABLE MODELS
India
0
∞× right
South Korea
9 · 1F
OPERATIONAL COMPUTE
India
127 MW · 4/6 MW-known
2.4× right
South Korea
310 MW · 2/2 MW-known
FUNDING
India
$2.3B
1.4× left
South Korea
$1.7B
AI ORGS
India
10
1.3× right
South Korea
13
SORTED BY LARGEST VISIBLE GAP NO NORMALIZED BAR LENGTHS; VALUES PRINTED DIRECTLY
note — India runs 1.4× more AI capital than South Korea. Whether that translates to frontier compute is what the next chart shows.
— ai-race-map · methodology @ /m
03 — Org capital concentration
India's top 3 absorb 72% of tracked funding
South Korea's top 3 hold 81% of tracked funding.
org upset
🇮🇳 India 10 orgs · $2.3B
top 1 30%
top 3 72%
biggest carrier: Fractal Analytics · $685M
🇰🇷 South Korea 13 orgs · $1.7B
top 1 50%
top 3 81%
biggest carrier: Rebellions · $850M
🇮🇳 India top 3 $1.6B
1 Fractal Analytics 30% of India tracked AI-native funding $685M 2 Uniphore 27% of India tracked AI-native funding $620M 3 Gupshup 15% of India tracked AI-native funding $340M
🇰🇷 South Korea top 3 $1.4B
1 Rebellions 50% of South Korea tracked AI-native funding $850M 2 FuriosaAI 16% of South Korea tracked AI-native funding $268M 3 Upstage 15% of South Korea tracked AI-native funding $260M
South Korea has more tracked orgs; India has the capital. HQ-BASED AI-NATIVE FUNDING ONLY · TOP-3 ROWS SHARE THE HEADLINE BASIS
Related comparisons
🇮🇳 India
vs
Canada 🇨🇦
🇮🇳 India
vs
United States 🇺🇸
🇰🇷 South Korea
vs
United States 🇺🇸
Updated 2026-05-08 India → South Korea → ← world map
pick left entity