MASS vs ONTO

908 Devices Inc. vs Onto Innovation Inc. — Valuation Comparison 2026

MASS

Measuring & Controlling Devices, NEC
908 Devices Inc.
Quality
7.9
out of 10
Value Trap
31
LOW
Price
$8.41
Last close
Models
12/13
Active
VS

ONTO

Measuring & Controlling Devices, NEC
Onto Innovation Inc.
Quality
10.0
out of 10
Value Trap
5
SAFE
Price
$258.24
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType MASS Fair ValueMASS Upside ONTO Fair ValueONTO Upside
Bayesian DCF Intrinsic $2.30 -72.6% $115.77 -55.2%
Earnings Power Value Intrinsic $7.02 +3.2% $30.85 -88.1%
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 MASS vs ONTO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MASS vs ONTO — Which Stock Is More Undervalued?

ONTO scores higher with a 10.0/10 quality rating vs MASS's 7.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing 908 Devices Inc. (MASS) and Onto Innovation Inc. (ONTO) 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.

MASS currently trades at $8.41 with a QOC of 7.9/10, while ONTO trades at $258.24 with a QOC of 10.0/10.

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).