FUSE (Fusemachines) Total Liabilities: $19.98 Mil (As of Mar. 2026)


FUSE Fusemachines Inc FUSE
8 GF Score
Price $0.99
! 3 Warning Signs
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What is Fusemachines Total Liabilities?

Fusemachines FUSE 8 Total Liabilities is $19.98 Mil as of Mar. 2026. GuruFocus rates FUSE with a GF Score™ of 8/100. The stock has 3 warning signs investors should review.

Fusemachines's Total Liabilities for the quarter that ended in Mar. 2026 was $19.98 Mil.

Fusemachines's quarterly Total Liabilities declined from Jun. 2025 ($32.75 Mil) to Dec. 2025 ($22.11 Mil) and declined from Dec. 2025 ($22.11 Mil) to Mar. 2026 ($19.98 Mil).

Fusemachines's annual Total Liabilities increased from Dec. 2023 ($11.82 Mil) to Dec. 2024 ($29.85 Mil) but then declined from Dec. 2024 ($29.85 Mil) to Dec. 2025 ($22.11 Mil).

Fusemachines Total Liabilities Historical Data

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The historical data trend for Fusemachines's Total Liabilities can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

Fusemachines Total Liabilities Chart

Fusemachines Annual Data
Trend Dec22 Dec23 Dec24 Dec25
Total Liabilities
7.23 11.82 29.85 22.11

Fusemachines Quarterly Data
Dec22 Dec23 Mar24 Sep24 Dec24 Mar25 Jun25 Dec25 Mar26
Total Liabilities Get a 7-Day Free Trial Premium Member Only 29.85 29.12 32.75 22.11 19.98
FUSE
8GF Score
Fusemachines Inc FUSE
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Fusemachines Total Liabilities Calculation

Total Liabilities are the liabilities that the company has to pay others. It is a part of the balance sheet of a company that shareholders do not own, and would be obligated to pay back if the company liquidated.

Fusemachines's Total Liabilities for the fiscal year that ended in Dec. 2025 is calculated as

Total Liabilities=Total Current Liabilities+Total Noncurrent Liabilities
=Total Current Liabilities+(Long-Term Debt & Capital Lease Obligation+Other Long-Term Liabilities
=20.049+(0.751+1.169
+NonCurrent Deferred Liabilities+PensionAndRetirementBenefit+NonCurrent Deferred Income Tax)
+0+0+0.143)
=22.11

Total Liabilities=Total Assets (A: Dec. 2025 )-Total Equity (A: Dec. 2025 )
=7.536--14.576
=22.11

Fusemachines's Total Liabilities for the quarter that ended in Mar. 2026 is calculated as

Total Liabilities=Total Current Liabilities+Total Noncurrent Liabilities
=Total Current Liabilities+(Long-Term Debt & Capital Lease Obligation+Other Long-Term Liabilities
=18.13+(0.689+1.08
+NonCurrent Deferred Liabilities+PensionAndRetirementBenefit+NonCurrent Deferred Income Tax)
+0+0+0.143)
=19.98

Total Liabilities=Total Assets (Q: Mar. 2026 )-Total Equity (Q: Mar. 2026 )
=4.944--15.033
=19.98

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

Frequently Asked Questions Learn more about Total Liabilities →
What does a Total Liabilities of $19.98 Mil mean?
Fusemachines (FUSE) has a Total Liabilities of $19.98 Mil as of Mar. 2026. The total amount of liabilities as recorded on a company's balance sheet. View historical data for Fusemachines and its competitors.
Is Fusemachines' Total Liabilities too high?
Fusemachines' current Total Liabilities is $19.98 Mil. Overall, Fusemachines has a GF Score™ of 8/100, reflecting its overall financial health beyond just this single metric.
How does Fusemachines' Total Liabilities compare to LGCL and CNTMD?
Fusemachines' Total Liabilities of $19.98 Mil can be compared against companies in the Software industry. See the competitive comparison table and distribution chart on this page for a detailed peer-by-peer breakdown.
What is a good Total Liabilities for a Software company?
A good Total Liabilities depends on the Software industry context. However, Total Liabilities should not be evaluated in isolation — investors should consider it alongside profitability, growth, and financial strength metrics. Use the industry distribution chart on this page to see where any company falls relative to its peers.
What does a high Total Liabilities mean?
A high Total Liabilities can signal that a stock is expensive relative to its fundamentals. The total amount of liabilities as recorded on a company's balance sheet. View historical data for Fusemachines and its competitors. Fusemachines's current Total Liabilities is $19.98 Mil. However, context matters — high-growth companies often justify higher valuations. Always evaluate alongside other metrics like GF Score™ and GF Value™.
Is Fusemachines stock overvalued right now?
Fusemachines (FUSE) has a current Total Liabilities of $19.98 Mil. The current Total Liabilities is $19.98 Mil. Fusemachines' overall GF Score™ is 8/100 with 3 warning signs to review. Investors should evaluate multiple metrics — including profitability, growth, and financial strength — before making a decision.
How is Total Liabilities calculated?
Total Liabilities is calculated from a company's financial statements. For Fusemachines (FUSE), the current Total Liabilities is $19.98 Mil as of Mar. 2026. GuruFocus calculates this using data sourced from SEC filings and annual reports. See the calculation section and 30-year financial data on this page for the full breakdown.

Fusemachines Business Description

Address 251 West 30th Street, 5th Floor, New York, NY, USA, 10001
Fusemachines Inc is a provider of enterprise AI solutions, offering products such as AI Studio, AI Engines, and AI Agents, along with supporting services across various industries. Its solutions are supported by a talent pool from underserved communities, enabling scalable and high-quality AI delivery while promoting access to AI. The Company serves clients across industries, including healthcare, media, technology, and government, helping address challenges such as improving forecasting accuracy, reducing data entry errors, automating recruitment, and detecting fraud. Its product suite includes AI Studio, AI Engines, and AI Agents, designed to build, deploy, and scale AI solutions, and it operates in Nepal and the United States.
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