What an AVM actually does
An AVM ingests two streams: the target property's attributes (address, beds, baths, square footage, lot size, year built) and a comparable-sales pool drawn from the surrounding geography and recent time window. It then runs one or several regressions to produce a single point estimate plus a confidence band.
The four regression families you'll see referenced in vendor methodology docs:
- Linear regression on comps. Fits a line through recent sale prices vs property attributes. Cheap, transparent, accurate in homogeneous tract subdivisions; falls apart in mixed-stock neighborhoods.
- Hedonic regression. Prices each feature independently — an extra bath is worth $X, an extra 1,000 ft² is worth $Y. Better at atypical homes than plain linear.
- Gradient-Boosted Trees (XGBoost / LightGBM). Non-linear ensembles that capture interactions (a pool is worth more in Miami than Buffalo). State of the art for Zestimate, HouseCanary, Quantarium, CoreLogic.
- Vision-based condition adjustment. New since 2024. The model looks at listing photos and adjusts down for "fair" or "poor" condition. Twellie's stack uses photo condition model for this layer.
Each architecture has its own failure mode. The honest vendors publish their median absolute error (MdAE) — the median of the absolute percentage error across a benchmark set of recent sales.
Why AVMs are not appraisals
A formal appraisal is a USPAP-compliant report from a licensed human appraiser who physically visits the property, applies the three USPAP approaches (sales-comparison, cost, income), and produces a defensible 30–50 page document. AVMs are statistical, not human-judgment, which is why a lender funding a mortgage requires the appraisal — not the AVM — for the loan file.
The two are complementary, not interchangeable. An AVM is fast, cheap, and good enough for screening properties before you visit. An appraisal is slow, costs $400–$700, and is the legal benchmark for the loan and any tax-appeal or estate settlement.
For the long version of this comparison see AVM vs Appraisal vs Zestimate.
Typical AVM accuracy
| AVM | Median Absolute Error | Tier |
|---|---|---|
| Quantarium / HouseCanary | 3–5% | Lender-grade |
| CoreLogic | 4–6% | Lender-grade |
| Redfin Estimate (off-market) | ~6.7% | Free consumer |
| Zillow Zestimate (off-market) | ~7.5% | Free consumer |
| Twellie | ~7% | Paid consumer + photo + report |
| Formal appraisal | 1–3% | Legal benchmark |
Two things to remember when reading these numbers:
- Active-listing accuracy is much better than off-market. Zillow's headline 1.9% MdAE is for active listings, where the model has the listing photos and recent comp data. Off-market — a home that hasn't sold in 8 years — is the harder problem and the number that matters when you're shopping.
- National averages hide huge variance. Every AVM is dramatically less accurate in markets with thin sale volume, atypical homes, or sparse public-records data. Rural Vermont is harder than tract Phoenix, and the confidence band reflects that.
When an AVM is the right tool
- Screening listings before you visit — is this in budget?
- Sanity-checking a list price against the comparable set
- Tax-appeal preparation, paired with a formal appraisal
- Pre-offer pricing, paired with the confidence band
When it isn't
- Loan funding. Lender requires a USPAP appraisal.
- Legal proceedings (divorce, estate, eminent-domain). Need an appraisal.
- Atypical property. A custom log home on 40 acres has no comps the AVM trusts. The confidence band will be wide; treat the number as a placeholder, not a value.
- Stale public records. If the county assessment is 8 years old and the home has been renovated since, every AVM trained on that record will inherit the staleness.
The right read on any AVM number is "point estimate plus a band". A $487,500 AVM with a $40k confidence band is telling you the real market value lives somewhere in the $447k–$527k window. That window is your negotiating range — not the headline number.
