AYTU vs AZTR

Aytu BioPharma, Inc. vs Azitra Inc — Valuation Comparison 2026

AYTU

Pharmaceutical Preparations
Aytu BioPharma, Inc.
Quality
6.0
out of 10
Value Trap
24
SAFE
Price
$2.29
Last close
Models
12/13
Active
VS

AZTR

Pharmaceutical Preparations
Azitra Inc
Quality
4.3
out of 10
Value Trap
44
WARN
Price
$0.23
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType AYTU Fair ValueAYTU Upside AZTR Fair ValueAZTR Upside
Bayesian DCF Intrinsic $2.22 -2.9% $0.38 +66.8%
Earnings Power Value Intrinsic $6.38 +178.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.12 -95.4% $0.04 -81.5%
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 AYTU vs AZTR — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

AYTU vs AZTR — Which Stock Is More Undervalued?

AYTU scores higher with a 6.0/10 quality rating vs AZTR's 4.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Aytu BioPharma, Inc. (AYTU) and Azitra Inc (AZTR) 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.

AYTU currently trades at $2.29 with a QOC of 6.0/10, while AZTR trades at $0.23 with a QOC of 4.3/10.

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).