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First Lithium Limited (FL1) Fair Value & Analysis

Basic Materials · AU · Market cap A$15.2M

PriceA$0.1400
Fair ValueA$0.0300
Upside-78.6%
Quality91/100
Evidence: Low Range A$0.0200 – A$0.0500

Fair value as of: Jun 26, 2026

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Analysis

First Lithium Limited (FL1) currently trades at A$0.1400, while our model-based Fair Value estimate is A$0.0300 — implying the stock looks roughly 78.6% overvalued today. We read business quality at 91/100 (high quality), in the Basic Materials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).

About the company

First Lithium Limited engages in the exploration and development of minerals properties in Mali. The company holds 100% interests in the Mali Lithium Project that includes two lithium bearing permits, including Faraba and Gouna covering an area of 17,500 hectares located in Mali. First Lithium Limited is based in Perth, Australia.

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Frequently asked questions

Is First Lithium Limited (FL1) undervalued?
As of Jun 26, 2026, our model estimates a fair value of A$0.0300 versus a price of A$0.1400 — about −79% (overvalued). Model-based estimate, not financial advice.
What is the fair value of FL1?
Our 21-model fair value for First Lithium Limited is A$0.0300 (as of Jun 26, 2026), built from audited fundamentals. The current price is A$0.1400.
What is the quality score of FL1?
First Lithium Limited has a Quality Score of 91/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.