SMXT vs SUNE

Solarmax Technology Inc. vs SUNation Energy, Inc. — Valuation Comparison 2026

SMXT

Construction - Special Trade Contractors
Solarmax Technology Inc.
Quality
5.9
out of 10
Value Trap
12
SAFE
Price
$0.55
Last close
Models
10/13
Active
VS

SUNE

Construction - Special Trade Contractors
SUNation Energy, Inc.
Quality
6.0
out of 10
Value Trap
38
LOW
Price
$1.36
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType SMXT Fair ValueSMXT Upside SUNE Fair ValueSUNE Upside
Bayesian DCF Intrinsic $0.11 -79.4% $4.66 +242.6%
Earnings Power Value Intrinsic $0.62 +12.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.47 -14.3% $5.60 +311.5%
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 SMXT vs SUNE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

SMXT vs SUNE — Which Stock Is More Undervalued?

SUNE scores higher with a 6.0/10 quality rating vs SMXT's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Solarmax Technology Inc. (SMXT) and SUNation Energy, Inc. (SUNE) 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.

SMXT currently trades at $0.55 with a QOC of 5.9/10, while SUNE trades at $1.36 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).