A home can show one value on Redfin and another on Zillow even when both websites are looking at the same address. That is not necessarily an error. Redfin Estimate and Zillow Zestimate are separate automated valuation models built from different data pipelines, update schedules, algorithms, and property facts.
The practical mistake is treating either number as an appraisal. Both companies frame their automated values as estimates. They can be useful for tracking a property and forming an initial range, but a real transaction price depends on the property, market, buyer demand, financing, condition, and comparable sales.
What the Redfin Estimate is
Redfin describes the Redfin Estimate as a calculation of an individual home’s market value. The model uses data from multiple listing services, property information, neighborhood data, and a proprietary machine-learning system.
Redfin currently says the estimate is updated daily for homes that are listed for sale and weekly for off-market homes.
What the Zestimate is
Zillow’s Zestimate is also an automated home-value estimate based on public, proprietary, and user-submitted property data and market information. Zillow updates its model as new information becomes available.
The two models do not need to agree because they are not using identical inputs or identical mathematics.
Why MLS access matters to Redfin
Redfin emphasizes that it is a real-estate brokerage with direct access to multiple listing services in the markets where it operates. That allows its model to use detailed listing and sale information.
MLS access can improve the freshness and detail of market data, especially for actively listed homes. It still does not guarantee that every property fact is complete or that the algorithm understands an unrecorded renovation.
Why the estimates differ more on off-market homes
Redfin’s current published error rates are much lower for on-market homes than off-market homes. As of the latest current page, Redfin reports a median error rate around 1.85% for homes for sale and around 7.27% for off-market homes.
The reason is intuitive: a listed property has fresh listing details, photos, seller disclosures, recent pricing decisions, and more direct market information. An off-market property can go years without new public data.
Median error rate does not mean every home is within that percentage
A median error rate means half of the estimates are closer than the stated threshold and half are farther away. It does not promise that your specific home is within that range.
A unique property, thin local market, rapid neighborhood change, or outdated home facts can produce much larger differences.
Property facts are a major source of disagreement
If Zillow believes a home has 2,100 square feet and Redfin shows 1,850, their estimates can diverge even if both models behave perfectly relative to their data.
Check bedroom count, bathroom count, square footage, lot size, property type, construction year, and recent sale history on both sites before trying to explain the value difference.
Renovations are difficult for automated models
A fully renovated kitchen, new roof, additional bathroom, finished basement, or high-quality addition may not immediately appear in public records or MLS data for an off-market property.
Conversely, a website can display a feature that no longer exists or was incorrectly entered. Automated models are only as useful as the data reaching them.
Comparable sales can be interpreted differently
Valuation models need to decide which nearby homes are actually comparable. A model may give more weight to recent sales, distance, property size, school district, view, street type, or other variables.
Two reasonable algorithms can therefore choose different comparable sets and arrive at different values.
Why listing status changes the estimate
When a home is listed, the asking price itself, updated MLS data, and fresh property information become part of the market picture. Both automated systems can react to that new information.
That does not mean an estimate simply copies the listing price. It means the model has more current evidence than it had when the home was off-market.
Do not average Redfin and Zillow and call it an appraisal
If Redfin says $510,000 and Zillow says $545,000, taking the midpoint produces $527,500. That number looks precise but has no independent valuation logic behind it.
A better response is to investigate why the estimates differ and compare recent local sales manually.
When the estimates are useful
Automated estimates are useful for monitoring broad changes, getting a quick starting range, comparing a property with nearby homes, and identifying when recorded property facts may be wrong.
They can also help homeowners begin a conversation with a real-estate professional or appraiser.
When they are not enough
For a purchase offer, refinance, estate matter, tax dispute, divorce, or other high-stakes decision, an automated website estimate may not be sufficient. Lenders and courts can require formal appraisals or other qualified valuations.
A local agent’s comparative market analysis can also provide property-specific context that an algorithm cannot see.
Example: a renovated home
Suppose a home sold eight years ago in dated condition and has since received $120,000 of renovations. The public record still shows the same square footage, bedroom count, and bathroom count. One model may infer some improvement from nearby sales while another remains conservative.
Neither website has physically inspected the renovation. A buyer walking through the property has information the algorithms do not.
Example: a busy street
Two otherwise similar homes can have different market appeal because one faces a major road. Redfin says its model can consider factors such as whether a home is on a busy street, but the real impact can vary by market and exact property position.
A model’s adjustment may still differ from what current buyers actually demand.
Use sold comps, not only active listings
Active listings show seller expectations. Sold properties show where buyers and sellers actually completed transactions.
For a manual comparison, prioritize recent sales with similar property type, size, condition, location, lot characteristics, and school or neighborhood context.
What to do when Zillow is much higher
Check whether Zillow has more favorable property facts, whether Redfin is missing a renovation, whether one model is using a stale record, or whether the local market has changed quickly.
Do not automatically assume the higher estimate is more accurate because it is more appealing.
What to do when Redfin is much higher
Run the same process in reverse. Inspect the facts, comparable sales, listing history, and recent local price trend.
A higher estimate should be supported by better evidence, not by preference.
If you are deciding whether the purchase price fits your household, How to Compare the Cost of Renting vs. Buying explains why estimated market value and affordability are separate questions.
A practical comparison checklist
- Record the current Redfin Estimate and Zestimate.
- Check the update date where available.
- Compare property facts on both sites.
- Review recent nearby sold properties.
- Separate active listing prices from completed sales.
- Adjust for renovations, condition, traffic, view, lot, and unique features.
- Use an appraiser or qualified local professional when the decision requires formal value.
Bottom line
Redfin Estimate and Zillow Zestimate can disagree because they are different automated valuation systems using different data and modeling choices. The disagreement is useful information: it tells you the property’s value deserves more investigation. Check property facts, recent sold comps, condition, and local context before treating either estimate as a transaction price.
This article was prepared using Redfin’s current Redfin Estimate methodology and accuracy page and its current Estimate FAQ. Redfin itself says the estimate is a starting point and not an appraisal. Zillow’s Zestimate methodology can likewise change as its model and data are updated.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.
Track changes instead of reacting to one day’s estimate
One automated estimate can move because new sales entered the model or property facts changed. If you are monitoring a home over time, record the estimates monthly rather than reacting to every update.
A trend supported by actual neighborhood sales is more informative than a single unexplained algorithmic jump.