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BLLN

BillionToOneB
Nasdaq / Health Care Equipment & Services
Last Price
At close
2026-08-01
View Chart
Current thesis
The strongest bull argument is that BillionToOne is already showing uncommon medtech/molecular-diagnostics operating leverage: Q1 combined 84% revenue growth, higher ASP, improving gross margin, positive operating income, positive ex-capex operating cash flow, and a second upward 2026 guidance reset within a few months [#SEC-8K-2026-05-06] [#SEC-8K-2026-03-04].
Posture
Constructive
Lead driver
Value
What changed
Next scheduled catalyst: earnings 2026-08-05 · AMC.
What can break
Capacity expansion raises utilization risk: the June 2026 lease supports demand, but under-absorbed new lab capacity would dilute operating leverage if volume growth slows [#8-K-2026-06-29].
Momentum
98
Value
51
Sentiment
25
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $112.00 · Bull $136.00 · Bear $92.00
Earnings
2026-08-05 · AMC
Data freshness
Prices
As of 2026-08-01
Fundamentals
As of 2026-07-31 • Vendor: Data Vendor v1
Scores
As of 2026-08-01 • Model: HYBRID_IC_RP
AI Memo
As of 2026-07-01 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-08-01
Supporting evidence
What
Grade B · Constructive
Confidence Medium · Net Neutral
Target $124.57
Why
Momentum98 · Δ7d -0.2
Value51 · Δ7d -0.0
Sentiment25 · Δ7d -8.1
So what
Strength-led posture (Net Neutral). Favor watchlist adds and disciplined entries.
Lead driver: Value · See fundamentals
Momentum
98
10% active weight
Current posture
7d trendFlat
Δ7d
-0.2
Δ21d
+1.8
Value
51
40% active weight
Current posture
7d trendFlat
Δ7d
-0.0
Δ21d
+0.0
Sentiment
25
49% active weight
Current posture
7d trendSoftening
Δ7d
-8.1
Δ21d
-11.3
Why this grade

Composite grade B. Momentum 98.2 / Value 50.8 / Sentiment 25.4

Fundamentals (TTM)
As of 2026-07-31
Market Cap
$6.37B
Beta
-
Shares Out
46M
P/E (TTM) · Derived
2175.8
P/S (TTM)
-
P/FCF (TTM)
-
Rev YoY
+83.8%
EPS YoY
-479.9%
Gross Margin
+70.4%
Op Margin
-
Net Debt
-$387.08M
Current Ratio
10.92
As of 2026-08-01 • Updated nightlySource: Internal modelMethodology