Is Brand-Erbisdorf expensive compared to Bundesrepublik Deutschland?

Compare the median €/m² on this page to the same figure on the Bundesrepublik Deutschland page to see relative pricing.

How have prices changed in Brand-Erbisdorf?

The 12-month trend table above shows monthly medians. A multi-month rise or fall tells you whether the market is heating up or cooling.

Where are the cheapest areas in Brand-Erbisdorf?

See the sub-locations table above, entries are sorted by listing volume; visit each sub-area page for its own median price.

How does Seeki calculate these figures?

We compute the median of price_eur / floorage across all published listings scoped to this location. We use median rather than mean to avoid distortion from outliers.

Brand-Erbisdorf, Average price per m²

Name: Average price per m² in Brand-Erbisdorf
Creator: Seeki
License: https://seeki.eu/terms

€1,931/m²

The median price per m² is currently €1,931. Data is updated regularly from public listings.

Budget (EUR)

€500,000

€50,000€1,025,000€2,000,000

What does your budget get you here?

≈ 258 m²

8 bedrooms

€1,931/m²

Quality of life breakdown

Transit0
Walkability0
Amenities0
Family0
Cultural0
Green space0
Noise100
Flood risk100
Economic health85

By property type

House€1,931/m²

Recent listings in Brand-Erbisdorf:

Sample listings

Frequently asked questions

Is Brand-Erbisdorf expensive compared to Bundesrepublik Deutschland?: Compare the median €/m² on this page to the same figure on the Bundesrepublik Deutschland page to see relative pricing.
How have prices changed in Brand-Erbisdorf?: The 12-month trend table above shows monthly medians. A multi-month rise or fall tells you whether the market is heating up or cooling.
Where are the cheapest areas in Brand-Erbisdorf?: See the sub-locations table above, entries are sorted by listing volume; visit each sub-area page for its own median price.
How does Seeki calculate these figures?: We compute the median of price_eur / floorage across all published listings scoped to this location. We use median rather than mean to avoid distortion from outliers.