HON vs MMM

Honeywell International Inc. vs 3M Company — Valuation Comparison 2026

HON

Conglomerates
Honeywell International Inc.
Quality
8.6
out of 10
Value Trap
8
SAFE
Price
$233.00
Last close
Models
13/13
Active
VS

MMM

Conglomerates
3M Company
Quality
6.6
out of 10
Value Trap
Price
$152.85
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType HON Fair ValueHON Upside MMM Fair ValueMMM Upside
Bayesian DCF Intrinsic $55.09 -76.4% $47.81 -68.7%
Earnings Power Value Intrinsic $62.59 -73.1% $70.15 -54.1%
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 HON vs MMM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

HON vs MMM — Which Stock Is More Undervalued?

HON scores higher with a 8.6/10 quality rating vs MMM's 6.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Honeywell International Inc. (HON) and 3M Company (MMM) 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.

HON currently trades at $233.00 with a QOC of 8.6/10, while MMM trades at $152.85 with a QOC of 6.6/10.

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).