BZFD vs GSAT

BuzzFeed, Inc. vs Globalstar, Inc. — Valuation Comparison 2026

BZFD

Communications Services, NEC
BuzzFeed, Inc.
Quality
4.2
out of 10
Value Trap
56
WARN
Price
$1.63
Last close
Models
10/13
Active
VS

GSAT

Communications Services, NEC
Globalstar, Inc.
Quality
7.4
out of 10
Value Trap
24
SAFE
Price
$84.21
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BZFD Fair ValueBZFD Upside GSAT Fair ValueGSAT Upside
Bayesian DCF Intrinsic $0.35 -55.9% $62.21 -26.1%
Earnings Power Value Intrinsic $0.86 -99.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $2.09 +28.4% $24.27 -71.2%
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 BZFD vs GSAT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BZFD vs GSAT — Which Stock Is More Undervalued?

GSAT scores higher with a 7.4/10 quality rating vs BZFD's 4.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing BuzzFeed, Inc. (BZFD) and Globalstar, Inc. (GSAT) 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.

BZFD currently trades at $1.63 with a QOC of 4.2/10, while GSAT trades at $84.21 with a QOC of 7.4/10.

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).