LIVN vs QTI

LivaNova PLC vs QT Imaging Holdings, Inc. — Valuation Comparison 2026

LIVN

Electromedical & Electrotherapeutic Apparatus
LivaNova PLC
Quality
8.7
out of 10
Value Trap
17
SAFE
Price
$73.04
Last close
Models
13/13
Active
VS

QTI

Electromedical & Electrotherapeutic Apparatus
QT Imaging Holdings, Inc.
Quality
4.5
out of 10
Value Trap
18
SAFE
Price
$5.00
Last close
Models
8/13
Active

Model-by-Model Comparison

ModelType LIVN Fair ValueLIVN Upside QTI Fair ValueQTI Upside
Bayesian DCF Intrinsic $25.26 -65.4% $0.93 -81.5%
Earnings Power Value Intrinsic $26.31 -64.0% $0.20 -96.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for LIVN vs QTI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LIVN vs QTI — Which Stock Is More Undervalued?

LIVN scores higher with a 8.7/10 quality rating vs QTI's 4.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing LivaNova PLC (LIVN) and QT Imaging Holdings, Inc. (QTI) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

LIVN currently trades at $73.04 with a QOC of 8.7/10, while QTI trades at $5.00 with a QOC of 4.5/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).