funder-graph

FundersCA

Grants paid by Gilbert Michael Meyer Foundation

EIN 81-2373292 · Los Angeles, CA · Form 990-PF, Part XV · NTEE T22

Gilbert Michael Meyer Foundation of Los Angeles, CA (EIN 81-2373292) reported 9 grants paid totaling $619,000 to 5 recipients in tax years 2018–2022, on Form 990-PF, Part XV. Derived from IRS e-file data, dataset version 2026.09.0, built 2026-09-03.

Grants paid

$619,000

9 grants

Recipients

5

distinct organizations

Tax years

2018–2022

5 filings in the corpus

By tax year

Grants by tax year, as the same figures
Tax yearGrants paidAmount paidApproved for future
20181$1,000
20191$1,000
20201$1,000
20211$1,000
20225$615,000

Top recipients

The 5 recipients receiving the most from Gilbert Michael Meyer Foundation, by grants paid, out of 5 distinct recipients.

Recipients ranked by total grants paid
RecipientMatchLocationGrantsTotal paidLatest year
Stephen Siller Tunnel to Towers Found 02-0554654CStaten Island, NY1$500,0002022
Smile Train 13-3661416BNew York, NY5$104,0002022
Catholic Charities of Santa Clara County 94-2762269BSan Jose, CA1$5,0002022
Doctors Without BordersUNew York, NY1$5,0002022
Downtown Streets Team 20-5242330CSan Jose, CA1$5,0002022

Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.

Every grant

All 9 grant rows this organization reported, most recent first.

Grants reported by Gilbert Michael Meyer Foundation
Tax yearRecipientMatchAmountTypePurposeSource filing
2022Stephen Siller Tunnel to Towers Found Staten Island, NYC$500,000paidTO PROVIDE GENERAL ASSISTANCE202311239349101771
2022Smile Train New York, NYB$100,000paidTO PROVIDE GENERAL ASSISTANCE202311239349101771
2022Downtown Streets Team San Jose, CAC$5,000paidTO PROVIDE GENERAL ASSISTANCE202311239349101771
2022Doctors Without Borders New York, NYU$5,000paidTO PROVIDE GENERAL ASSISTANCE202311239349101771
2022Catholic Charities of Santa Clara County San Jose, CAB$5,000paidTO PROVIDE GENERAL ASSISTANCE202311239349101771
2021Smile Train New York, NYB$1,000paidTO PROVIDE FREE CLEFT SURGERY AND COMPREHENSIVE CLEFT CARE TO CHILDREN WORLDWIDE202242279349100634
2020Smile Train New York, NYB$1,000paidTO PROVIDE FREE CLEFT SURGERY AND COMPREHENSIVE CLEFT CARE TO CHILDREN WORLDWIDE202101309349101530
2019Smile Train New York, NYB$1,000paidTO PROVIDE FREE CLEFT SURGERY AND COMPREHENSIVE CLEFT CARE TO CHILDREN WORLDWIDE202022069349100202
2018Smile Train New York, NYB$1,000paidTO PROVIDE FREE CLEFT SURGERY AND COMPREHENSIVE CLEFT CARE TO CHILDREN WORLDWIDE201911229349102011

Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.

Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.

Source filings

Every figure above is traceable to one of these IRS e-file returns by its OBJECT_ID.

Returns this page is derived from
FormTax yearPeriod endFiledSchemaIRS OBJECT_ID
990PF20222022-12-31not stated2022v5.0202311239349101771
990PF20212021-12-31not stated2021v4.0202242279349100634
990PF20202020-12-31not stated2020v4.0202101309349101530
990PF20192019-12-31not stated2019v5.0202022069349100202
990PF20182018-12-31not stated2018v3.1201911229349102011

Derived from IRS Form 990-PF e-file XML; recipient identities from the IRS Exempt Organizations Business Master File. Dataset version 2026.09.0, built 2026-09-03. The same rows as Parquet: manifest; as JSON: /api/funders/812373292.json.

The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.

This is informational only, derived from public data on the dates shown. It is not an eligibility determination, and not legal, tax, or accounting advice. Verify against the official source before relying on it.