Transloadit Research
We publish the measurements behind practical choices in upload reliability, encoding quality, file size, latency, cost, and compute. Every report separates what the data shows from what it cannot prove.
Published report
October 2026 dataset
Output size, Robot time, and SSIM for 882 Assemblies that optimize and re-encode a public image corpus across JPEG, PNG, GIF, WebP, SVG, and AVIF.
882
Assemblies
3
runs per parameter set
54
source files
What the first dataset shows
JPEG, default settings
84.7%
Median size reduction for camera JPEGs with the Image Optimize Robot’s default settings.
WebP versus JPEG
25.7%
Fewer bytes than JPEG when both are encoded at quality 75 from the same lossless sources.
Research program
Our research program focuses on decisions where a benchmark can replace a vague best practice with a measurable tradeoff.
Video delivery
Measure wall-clock encoding time, visual quality, output size, and processing cost for practical adaptive-streaming ladders.
Codec efficiency
Compare perceptual quality and structural similarity against bytes delivered for modern and established codecs.
Upload reliability
Test completion rate, transferred bytes, and recovery time through packet loss, disconnects, and browser restarts.
Format coverage
Run a documented corpus through preview pipelines and report successful rendering, fidelity issues, and failure classes.
Recognition quality
Score text and speech outputs against reviewed references, broken down by language, media conditions, and error type.
Delivery architecture
Compare first-request latency, cache behavior, bytes processed, and cost for eager and on-demand transformations.
Compute efficiency
Quantify avoided compute and estimated emissions when derivatives are reused instead of transformed again.
Publication standard
