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What we read

Janoshik Analytical's public-tests database, Finnrick Analytics' published testing methodology and the headline figure of 7,164 tests across 205 vendors as of April 2026, Peptide Protocol Wiki's transparency critique of Finnrick's lab-assignment policy, and approximately 80 r/Peptides comments between January 2024 and April 2026 that referenced specific Janoshik COA results. This is a data synthesis, not a first-hand audit.

The 43% headline

The single most-cited industry statistic comes out of Janoshik's 2024 reporting: of all peptide samples submitted to Janoshik for HPLC purity quantification in 2024, 43% failed to meet the purity claim on the vial label. That number is the closest thing the grey-market peptide industry has to an FDA Form 483 — a measurable, repeatable indictment of label accuracy at scale.

It is also generous to the industry. The 43% includes only samples that vendors or community members chose to submit for testing — a self-selected pool that skews toward vendors confident enough to face independent verification, or toward batches a buyer specifically suspected. The unmeasured population (vendors that never submit, customers that never test) is almost certainly worse.

Where the gap concentrates

Three patterns dominate the failed-purity dataset.

1. Identity fraud, not just dilution. In 2025, Janoshik flagged that roughly 23% of retatrutide samples submitted for analysis contained exendin-4 analogs instead of authentic retatrutide. This is not a purity gap — the molecule itself is wrong. Exendin-4 is a related GLP-1 agonist that costs a vendor a fraction of what retatrutide costs to synthesize correctly. For the buyer, identity fraud is harder to detect than under-purity and impossible to verify without mass-spec.

2. Tier-correlated dishonesty. The samples failing badly cluster in a specific vendor band: small operators claiming 99%+ purity whose actual HPLC results came back at 71–91%. The vendors at the top of community lists rarely fail by more than 1–2 percentage points; the vendors at the bottom miss by 8–28 points and frequently flunk identity confirmation too. This pattern argues against the popular advice "any COA is enough." A COA from a low-tier vendor is more likely to be wrong than absent.

3. Generic-batch COAs. A persistent failure mode is the vendor that publishes one COA and reuses it across batches that share nothing but the SKU label. Janoshik's QR-verified COAs are designed to defeat this — the QR resolves to a specific vial test on Janoshik's servers, not a PDF a vendor can edit. Vendors publishing non-Janoshik COAs without batch IDs or lot numbers are particularly suspect.

What the data does not show

Two limitations worth surfacing before drawing conclusions.

Self-selection bias. Janoshik tests what is sent to them. A vendor that refuses to submit batches to independent testing — or only submits favorable batches — does not appear in the failure rate. The 43% may be a floor.

Lab-assignment opacity in adjacent databases. Peptide Protocol Wiki has documented transparency concerns at Finnrick specifically: no published methodology for assigning samples to labs, no public handling of inter-lab discrepancies, no way to verify whether all results from a vendor's submissions are published. Finnrick's 7,164-test figure remains the largest dataset in the space, but its handling of adverse results is not auditable in the way Janoshik's QR-verified public-tests database is.

What this means for buyers

Three operating rules consistent with the data:

• Treat the COA as binary on identity, gradient on purity. A vendor that cannot produce mass-spec identity confirmation should be skipped without further analysis. A vendor with HPLC purity 1–2 points below claim is acceptable; 5+ points below is a vendor we would not buy from.
• Match the COA to a batch. A COA without a batch number, lot ID, or date matching your specific vial is not a COA — it is a marketing PDF.
• Prefer Janoshik QR over vendor-stated COAs when both are available. The QR resolves to a record outside the vendor's control.

We use a 1.5-percentage-point cross-lab tolerance on every audit on this site. Vendors whose batch COA differs from independent retesting by more than that figure get the gap surfaced in the audit notes and weighted into the COA-quality subscore.

What we did not read

This synthesis does not include private-lab results that vendors share only with verified buyers; communications on Discord servers behind invite-only walls; or non-English forums (r/Peptides, Peptide Protocol Wiki, and Janoshik's database are predominantly English-language). The next iteration of this analysis will incorporate the German-language harm-reduction forums where some retatrutide identity-fraud cases were first surfaced.

Sources

• Janoshik public tests database
• Finnrick Analytics — testing methodology
• Peptide Protocol Wiki — Finnrick transparency critique
• Peptide Protocol Wiki — Janoshik review