LFMD vs MMED

LifeMD, Inc. vs MiniMed Group, Inc. — Valuation Comparison 2026

LFMD

Health Information Services
LifeMD, Inc.
Quality
7.7
out of 10
Value Trap
6
SAFE
Price
$4.59
Last close
Models
12/13
Active
VS

MMED

Health Information Services
MiniMed Group, Inc.
Quality
1.6
out of 10
Value Trap
Price
$11.51
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType LFMD Fair ValueLFMD Upside MMED Fair ValueMMED Upside
Bayesian DCF Intrinsic $1.77 -61.4% $3.40 -70.5%
Earnings Power Value Intrinsic $3.89 -22.3% $5.20 -60.6%
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 LFMD vs MMED — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LFMD vs MMED — Which Stock Is More Undervalued?

LFMD scores higher with a 7.7/10 quality rating vs MMED's 1.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing LifeMD, Inc. (LFMD) and MiniMed Group, Inc. (MMED) 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.

LFMD currently trades at $4.59 with a QOC of 7.7/10, while MMED trades at $11.51 with a QOC of 1.6/10.

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).