TPVG vs TSLX

TriplePoint Venture Growth BDC vs Sixth Street Specialty Lending, — Valuation Comparison 2026

TPVG

Asset Management
TriplePoint Venture Growth BDC
Quality
6.1
out of 10
Value Trap
28
LOW
Price
$5.55
Last close
Models
11/13
Active
VS

TSLX

Asset Management
Sixth Street Specialty Lending,
Quality
6.6
out of 10
Value Trap
12
SAFE
Price
$17.35
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType TPVG Fair ValueTPVG Upside TSLX Fair ValueTSLX Upside
Bayesian DCF Intrinsic $0.50 -90.9% $10.24 -41.0%
Earnings Power Value Intrinsic $1.41 -74.7% $0.26 -98.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 TPVG vs TSLX — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

TPVG vs TSLX — Which Stock Is More Undervalued?

TSLX scores higher with a 6.6/10 quality rating vs TPVG's 6.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing TriplePoint Venture Growth BDC (TPVG) and Sixth Street Specialty Lending, (TSLX) 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.

TPVG currently trades at $5.55 with a QOC of 6.1/10, while TSLX trades at $17.35 with a QOC of 6.6/10.

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).