Chili's
U.S. · 1,209 locations
Chili's Grill & Bar, the flagship brand of publicly traded Brinker International (NYSE.
More about this list
EAT), operates 1,209 locations in this dataset — making it the largest casual dining chain in the U.S. by unit count after Applebee's, and notably one where roughly 80% of domestic units are company-owned rather than franchised, giving Brinker unusually direct control over real estate decisions and closure timing. The brand has been in a strategic inflection since 2023, posting consecutive quarters of positive same-store traffic growth driven by its viral 'Big Smasher' burger campaign and aggressive value positioning against fast-casual competitors, reversing years of net unit contraction that saw the footprint shrink from ~1,600 U.S. locations a decade ago. This dataset is essential for commercial real estate brokers tracking casual dining anchor tenancy in strip malls and power centers, food-service distributors like Sysco or US Foods optimizing delivery routing across Brinker's company-owned network, and private equity analysts benchmarking casual dining density against fast-casual encroachment in specific DMAs.
The file has all 1,209 locations across 49 states in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.
Need just some of them? Ask in your own words.
●Where the rows are

≡Sample Data Preview
| name | address | city | state | zip | phone | url | geo precision | county | county fips | address quality | country | latitude | longitude |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Chili's Grill and Bar Dimond Mall, AK | 800 E Dimond Blvd. '162' | Anchorage | AK | 99515 | (907) 646-7700 | https://www.chilis.com/locations/us/alaska/anchorage/dimond-mall | source | Anchorage Municipality | 02020 | complete | US | 61.14361 | -149.870919 |
| Chili's Grill and Bar Acworth, GA | 3339 Cobb Pkwy | Acworth | GA | 30101 | (770) 974-4558 | https://www.chilis.com/locations/us/georgia/acworth/acworth | source | Cobb County | 13067 | complete | US | 34.0349179 | -84.682682 |
| Chili's Grill and Bar White Marsh, MD | 8119 Honeygo Blvd. | Baltimore | MD | 21236 | (410) 933-0089 | https://www.chilis.com/locations/us/maryland/baltimore/white-marsh | source | Baltimore County | 24005 | complete | US | 39.371052 | -76.4665603 |
| Chili's Grill and Bar Dover, NH | 14 Weeks Lane | Dover | NH | 03820 | (603) 749-0939 | https://www.chilis.com/locations/us/new-hampshire/dover/dover | source | Strafford County | 33017 | complete | US | 43.222229 | -70.886877 |
| Chili's Grill and Bar Rapid City, SD | 2125 Haines Avenue | Rapid City | SD | 57701 | (605) 388-8100 | https://www.chilis.com/locations/us/south-dakota/rapid-city/rapid-city | source | Pennington County | 46103 | complete | US | 44.105825 | -103.222764 |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| name | Store name and number | 100% |
| address | Street address | 100% |
| city | City name | 100% |
| state | Two-letter state code | 100% |
| zip | 5-digit ZIP code | 100% |
| country | Country code (US) | 100% |
| phone | Store phone number | 100% |
| latitude | GPS latitude coordinate | 100% |
| longitude | GPS longitude coordinate | 100% |
| url | Url | 100% |
| geo_ | How exact the map point is: the source's own point, the street address, or the ZIP code's centre | 100% |
| county | County the location is in | 100% |
| county_ | Five-digit federal code of that county | 100% |
| address_ | Whether the street address is complete, missing a house number, or a PO box | 100% |
Rows filled is measured on every row of the delivered file.
✓Where this data comes from
This dataset is compiled from Chili's's own public store locator, the system behind the “find a store” page on their website.
September 14, 2026
File built
14 fields
Columns in the file
Fill measured
On every row of the delivered file
How we build and date every file: methodology.
Using ChatGPT, Claude or an API?
No setup needed. Ask ChatGPT or Claude your question about the Chili's Locations and give it this page: it can open https://locationlists.com/find?dataset=chilis-stores with the filters you need and show you the count and price.
Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.
How assistants ask
No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.
If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.
Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>
Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>
Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.
Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:
- Only Texas, the state with the most: https://locationlists.com/find?dataset=chilis-stores&state=TX
- Within 25 miles of Dallas, TX, the busiest area: https://locationlists.com/find?dataset=chilis-stores&near=Dallas+TX&radius=25
- Within a 30-minute drive of Dallas, TX: https://locationlists.com/find?dataset=chilis-stores&near=Dallas+TX&drive=30
- Every Quick Service & Fast Casual list combined, within 25 miles of Addison, TX: https://locationlists.com/find?category=quick-service-restaurant&near=Addison+TX&radius=25
- Each one's nearest Smoothie King Locations, in Texas, with miles: https://locationlists.com/find?dataset=chilis-stores&state=TX&relate=nearest&k=1&b.dataset=smoothie-king-stores&b.state=TX
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=chilis-stores - In plain words: "Chili's Locations in Texas": https://locationlists.com/find?q=Chili's+Locations+in+Texas
- In plain words: "Chili's Locations within 25 miles of Dallas, TX": https://locationlists.com/find?q=Chili's+Locations+within+25+miles+of+Dallas%2C+TX
Optional: connect for repeat use or wallet payments:
Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the Chili's Locations list.Your assistant will walk you through setup and show you the price before you pay.
For developers
At 1,209 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=chilis-stores. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works
?Frequently Asked Questions
How does Chili's primarily company-owned model affect how I should use this data compared to a franchise-heavy chain like Applebee's?
Because roughly 80% of Chili's domestic units are company-owned, location decisions (openings, closures, remodels) are made centrally by Brinker International, meaning the footprint reflects a single corporate real estate strategy rather than hundreds of independent franchisee decisions. This makes the data especially useful for predicting closure patterns or expansion corridors — Brinker has systematically exited low-traffic trade areas since 2017. If you need a side-by-side overlay with Applebee's franchised footprint to identify markets where only one brand remains, LocationLists can run that overlap analysis as a custom project.
I'm a commercial real estate broker tracking casual dining vacancy risk in suburban power centers. How does Chili's recent performance change how I read this data?
Chili's reversed its multi-year traffic decline in late 2023, posting positive same-store sales growth through value-driven menu engineering and social media virality. This means the current 1,209-location footprint is more stable than it was during the 2018–2022 contraction period when Brinker closed roughly 400 underperforming units. However, the locations that survived that culling are concentrated in higher-traffic suburban corridors — cross-referencing this dataset with traffic count data will help you identify which remaining units sit in genuinely strong trade areas versus ones still at risk.
How does Chili's geographic density compare to other large casual dining brands, and can I benchmark it against fast-casual competitors?
With 1,209 locations, Chili's has roughly 25–30% fewer domestic units than Applebee's (~1,600) but significantly more than chains like TGI Friday's (~250 after its recent contraction) or Red Robin (~500). The more revealing comparison may be against fast-casual brands like Chipotle (~3,500 units), which now outnumber Chili's nearly 3:1 and increasingly compete for the same lunch occasion. LocationLists can build a custom density-ratio report comparing Chili's per-capita coverage against any fast-casual brand in our catalog, market by market.
I work for a broadline food distributor and need to optimize delivery routes to Chili's locations. Does this dataset support that?
Yes — every record includes latitude and longitude coordinates, which you can feed directly into route optimization software. Because Chili's company-owned model means a single purchasing relationship with Brinker's corporate supply chain team (primarily through their existing Sysco partnership), this data is especially useful for competing distributors mapping which Chili's clusters might be targetable if Brinker renegotiates contracts. The geographic coordinates let you calculate drive-time radiuses from your existing distribution centers.
Can this data help identify white-space markets where Chili's closed locations but demand may still exist?
Absolutely — this is one of the highest-value use cases. Brinker closed roughly 400 U.S. Chili's locations between 2017 and 2022, leaving significant gaps in markets like rural Texas, parts of the Midwest, and secondary Southern metros. By comparing this current 1,209-location dataset against historical location lists (which LocationLists can source as a custom engagement), you can identify specific trade areas where Chili's exited but population growth or competitive exits have since improved the demand picture — valuable intel for franchise developers or competing casual dining brands evaluating those same sites.
I'm a private equity analyst evaluating a potential casual dining investment. How does this dataset factor into my diligence?
The 1,209-location footprint is a post-rationalization baseline — Brinker already made the painful closures, so what remains is a leaner, higher-AUV portfolio. You can use this data to calculate unit-level trade area overlap with the target brand, identify markets where Chili's presence creates competitive pressure, and map co-tenancy patterns with retail anchors like Target (2,034+ locations in our catalog) or grocery chains. For a full competitive landscape overlay — Chili's vs. Applebee's vs. your target — LocationLists offers custom multi-brand overlap reports with market-level scoring.