Is STG or VSA more undervalued in 2026?

CirclFi compares Sunlands Technology Group (STG) and VisionSys AI Inc. (VSA) using 13 institutional-grade valuation models. STG has a Quality of Company score of 9.1/10 while VSA scores 4.9/10.

Which is a better buy — STG or VSA?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do STG and VSA valuations compare?

STG at $2.72 and VSA at $3.72 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

STG vs VSA Valuation Comparison 2026 — Intrinsic Value Analysis

STG

Education & Training Services

Sunlands Technology Group

Quality

9.1

out of 10

Value Trap

SAFE

Price

$2.72

Last close

Models

4/13

Active

VSA

Education & Training Services

VisionSys AI Inc.

Quality

4.9

out of 10

Value Trap

WARN

Price

$3.72

Last close

Models

4/13

Active

Model-by-Model Comparison

Model	Type	STG Fair Value	STG Upside	VSA Fair Value	VSA Upside
Bayesian DCF	Intrinsic	—	—	$1.06	-71.6%
Earnings Power Value	Intrinsic	—	—	$1.36	+78.2%
EROIC Spread	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	$3.59	+31.8%	$15.24	+309.6%
Dynamic NAV	Asset-Based	$5.50	+102.2%	—	—
PWERM	Option-Based	$•••.••	••.•%	$•••.••	••.•%
FTNN Topology	Relative	$•••.••	••.•%	$•••.••	••.•%

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STG vs VSA — Which Stock Is More Undervalued?

STG scores higher with a 9.1/10 quality rating vs VSA's 4.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Sunlands Technology Group (STG) and VisionSys AI Inc. (VSA) 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.

STG currently trades at $2.72 with a QOC of 9.1/10, while VSA trades at $3.72 with a QOC of 4.9/10.

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).