FIGR vs GEMI

Figure Technology Solutions, In vs Gemini Space Station, Inc. — Valuation Comparison 2026

FIGR

Capital Markets
Figure Technology Solutions, In
Quality
7.6
out of 10
Value Trap
Price
$34.73
Last close
Models
13/13
Active
VS

GEMI

Capital Markets
Gemini Space Station, Inc.
Quality
4.4
out of 10
Value Trap
Price
$5.20
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType FIGR Fair ValueFIGR Upside GEMI Fair ValueGEMI Upside
Bayesian DCF Intrinsic $6.59 -81.0% $1.75 -64.6%
Earnings Power Value Intrinsic $7.93 -77.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $18.17 -47.7% $2.57 -50.5%
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 FIGR vs GEMI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FIGR vs GEMI — Which Stock Is More Undervalued?

FIGR scores higher with a 7.6/10 quality rating vs GEMI's 4.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Figure Technology Solutions, In (FIGR) and Gemini Space Station, Inc. (GEMI) 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.

FIGR currently trades at $34.73 with a QOC of 7.6/10, while GEMI trades at $5.20 with a QOC of 4.4/10.

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).