When more than one lab tests the same batch, we line up their results side by side. When they match, it is the strongest signal you can get. When they do not, that is information too. Here is what these labs found — you decide.
2 independent labs tested this batch of Retatrutide from Qing Li Peptide.
Not enough data to compare
These labs did not report enough overlapping numbers to line up cleanly.
On the actual amount per vial, the labs were far apart (9.9 to 33.3 mg).
✓ Multi-Lab Verified
·
Poor · 5.2
The two badges above are our blended RV-score view: whether the scores agree, and the overall quality tier. The plain read at the top leads with the labs actual purity numbers, and the full per-lab table is below.
Retatrutide from Qing Li Peptide
batch Nov2,2025 · cross-tested by 2 independent labs
Independent labs agree on this batch within 0.5 RV-score points. Strong cross-validation.
✓ Batch identity basis: Same physical sample (Finnrick multi-lab program)
All records carry Finnrick (FNR-*) task IDs, meaning one physical vial was routed by Finnrick to multiple labs and each lab tested it independently. This is the strongest basis for 'same batch' — there's no batch heterogeneity between labs because there's no batch difference: it's the same vial.
Purity agrees, content diverges. Labs converge on purity (spread 0.45pp) but disagree on the actual amount (range 9.9–33.3 mg, CV 48.2%). The compound is what it claims to be — but how much is in the vial varies measurably between labs.
Reporting-basis mismatch or different denominator — investigate. One lab's measurement is more than 1.8× another's. Counterion plus residual water tops out around 1.3–1.5× even in bad cases, so a spread this large usually means the two labs aren't measuring the same thing — different denominator (per-mL vs per-vial), a dilution-factor mismatch, a decimal slip, or a sample-prep difference. The compound itself may be fine; the disagreement is about how it was quantified. Resolves once method/basis is surfaced per lab.
⇄ Weak-lot label — multiple products grouped together.
This page groups records by the vendor's batch label, but the records span 3 distinct labeled dose products (10mg, 20mg, 30mg). The aggregate Content Mean / Range / CV stats above mix different products; the per-dose breakdown below is what to read instead. Vendor batch labels like calendar dates often cover multiple physical lots and SKUs.
Per-dose breakdown — the meaningful view
Within each labeled dose, content should cluster tightly around the labeled amount (with some overfill). Cross-dose averages aren't a meaningful summary of this group.
10mg labeled — 2 tests
Moderate
Mean: 10.85 mg
Range: 9.90–11.80 mg
Variation: CV 8.8%
Labs: BTLabs
✓ consistent with label
20mg labeled — 1 test
Single test
Mean: 23.40 mg
Range: 23.40 mg
Variation: —
Labs: Krause Analytical
✓ consistent with label
30mg labeled — 1 test
Single test
Mean: 33.30 mg
Range: 33.30 mg
Variation: —
Labs: Krause Analytical
✓ consistent with label
Labs
2
Tests
4
RV Score Mean
5.20
RV Score Spread
0.00
Content Mean (mixes products — see above)
19.6 mg
⇄ Basis mismatch
Content Range (mixes products)
9.9–33.3 mg
CV 48.2%
Per-Lab Breakdown
All rows (Purity & Content vary, everything else constant): Testing 3.1 · Label 7.0 · Custody 4.3 · CI 10.0 · Method HPLC · RV 5.20
| Lab | Task | Test Date | Product (labeled) | RV | Purity | Content | Testing | Label | Custody | CI | Method |
|---|---|---|---|---|---|---|---|---|---|---|---|
| BTLabs | #FNR-4tprwpr | 10mg Retatrutide 10mg | 5.20 | 99.6% | 11.8 mg | 3.1 | 7.0 | 4.3 | 10.0 | HPLC ~ | |
| BTLabs | #FNR-kd6hdxz | 10mg Retatrutide 10mg | 5.20 | 99.5% | 9.9 mg | 3.1 | 7.0 | 4.3 | 10.0 | HPLC ~ | |
| Krause Analytical | #FNR-qfvnq4g | 20mg Retatrutide 20mg | 5.20 | 99.95% | 23.4 mg | 3.1 | 7.0 | 4.3 | 10.0 | HPLC ~ | |
| Krause Analytical | #FNR-aa6tpey | 30mg Retatrutide 30mg | 5.20 | 99.95% | 33.3 mg | 3.1 | 7.0 | 4.3 | 10.0 | HPLC ~ |
Why this matters: A single COA is one lab's answer from one method on one sample. Multiple labs reveal the pattern. When labs converge on the same answer, that's strong cross-validation. When they diverge — especially on content while agreeing on purity — the difference is often method-driven (different quantitation basis) but sometimes signals real product variation. ResearchVerify is the only platform that surfaces both cases automatically across thousands of cross-tests.