WKHS vs XPEV

Workhorse Group, Inc. vs XPeng Inc. — Valuation Comparison 2026

WKHS

Auto Manufacturers
Workhorse Group, Inc.
Quality
4.7
out of 10
Value Trap
12
SAFE
Price
$4.56
Last close
Models
9/13
Active
VS

XPEV

Auto Manufacturers
XPeng Inc.
Quality
7.7
out of 10
Value Trap
12
SAFE
Price
$16.44
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType WKHS Fair ValueWKHS Upside XPEV Fair ValueXPEV Upside
Bayesian DCF Intrinsic $0.05 -98.7% $13.14 -20.1%
Earnings Power Value Intrinsic $28.02 +77.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $3.72 -18.3%
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 WKHS vs XPEV — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

WKHS vs XPEV — Which Stock Is More Undervalued?

XPEV scores higher with a 7.7/10 quality rating vs WKHS's 4.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Workhorse Group, Inc. (WKHS) and XPeng Inc. (XPEV) 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.

WKHS currently trades at $4.56 with a QOC of 4.7/10, while XPEV trades at $16.44 with a QOC of 7.7/10.

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).