VIOT vs XWIN

Viomi Technology Co., Ltd vs XMAX, Inc. — Valuation Comparison 2026

VIOT

Furnishings, Fixtures & Appliances
Viomi Technology Co., Ltd
Quality
8.5
out of 10
Value Trap
20
SAFE
Price
$0.95
Last close
Models
10/13
Active
VS

XWIN

Furnishings, Fixtures & Appliances
XMAX, Inc.
Quality
6.0
out of 10
Value Trap
30
LOW
Price
$8.24
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType VIOT Fair ValueVIOT Upside XWIN Fair ValueXWIN Upside
Bayesian DCF Intrinsic $4.86 +410.5% $2.28 -72.4%
Earnings Power Value Intrinsic $0.32 -96.0%
EROIC Spread Intrinsic $5.47 +473.7% $1.10 -86.6%
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 VIOT vs XWIN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

VIOT vs XWIN — Which Stock Is More Undervalued?

VIOT scores higher with a 8.5/10 quality rating vs XWIN's 6.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Viomi Technology Co., Ltd (VIOT) and XMAX, Inc. (XWIN) 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.

VIOT currently trades at $0.95 with a QOC of 8.5/10, while XWIN trades at $8.24 with a QOC of 6.0/10.

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).