CMMB vs CNTA

Chemomab Therapeutics Ltd. vs Centessa Pharmaceuticals plc — Valuation Comparison 2026

CMMB

Biotechnology
Chemomab Therapeutics Ltd.
Quality
1.9
out of 10
Value Trap
6
SAFE
Price
$2.07
Last close
Models
8/13
Active
VS

CNTA

Biotechnology
Centessa Pharmaceuticals plc
Quality
5.9
out of 10
Value Trap
24
SAFE
Price
$39.81
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType CMMB Fair ValueCMMB Upside CNTA Fair ValueCNTA Upside
Bayesian DCF Intrinsic $0.55 -73.5% $11.91 -70.1%
Earnings Power Value Intrinsic $16.41 -58.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $0.07 -96.7% $0.01 -100.0%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for CMMB vs CNTA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CMMB vs CNTA — Which Stock Is More Undervalued?

CNTA scores higher with a 5.9/10 quality rating vs CMMB's 1.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Chemomab Therapeutics Ltd. (CMMB) and Centessa Pharmaceuticals plc (CNTA) 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.

CMMB currently trades at $2.07 with a QOC of 1.9/10, while CNTA trades at $39.81 with a QOC of 5.9/10.

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).