Milliseconds per label, whole retailer packets in one request, and PDFs that stay small. Pick a competitor and a workload — every chart below is a real, dated measurement you can reproduce.
Compare against
Output format
zpl.tools deployment
Labelary and the zpl.tools API are both hosted services — both lines carry the same network time.
Benchmark
Orderful retail compliance labels, a different label on every page.
Faster than Labelary
3.1×
The largest packet Labelary accepts, 50 pages: 129 ms vs 400 ms.
Per page in a 100-page packet
2 ms
PDF size at 100 pages
203.5 KB
Orderful style, PDF. Orderful retail compliance labels, a different label on every page.
The share of requests that returned 200. Labelary rejects a packet past its documented limits; the line drops to 0%.
Orderful style, PDF.
Orderful style, PDF.
Measured 2026-08-17. k6 drives every point, one request at a time. Client: k6, one request at a time. Both hosted engines measured in the same session from a Hetzner ccx13 (dedicated vCPU) in the fsn1 datacenter, Germany — network RTT included, the same for both sides. Local engines measured on a MacBook Pro (Apple Silicon), no network crossed; the zpl.tools, zebrash, BinaryKits and Neodynamic summaries carry over from the 2026-08-09 run, because no code in the render path changed between them. labelize was added on 2026-08-17 and measured on the same MacBook, at one page only — see below.
See the methodology — the corpora, the percentile tables, and how to repeat the run.
Free during beta: no page limits and no request limits.