---
title: "Benchmarks Deep Dive — Coming Pre-Launch"
slug: "benchmarks-deep-dive"
author: "Primate Intelligence"
date: "2026-05-22"
readTime: "Coming soon"
tags: ["Research"]
excerpt: "Our full benchmark methodology, numbers against YOLO / SAM / VLM baselines, and the rig we ran them on. In production — publishing ahead of public launch."
canonical: https://primateintelligence.ai/blog/benchmarks-deep-dive
---

## This piece is in production and coming pre-launch.

We're putting the final detail on our benchmark suite — the numbers that
back up how Primate Vision compares to YOLO, SAM-class detectors, and the
general-purpose VLMs that have dominated computer-vision posts this year.

When we publish, this page will cover:

- **The rig.** Hardware, model checkpoints, and seed values we ran on, so
  every number is reproducible.
- **The datasets.** Real footage from the use cases we care about — security
  cameras, drones, retail, robotics — plus the standard public benchmarks for
  cross-checking.
- **The metrics.** Where we win, where we don't, and the specific scene
  categories where JEPA-based prediction beats reconstruction-based models.
- **The cost story.** Per-frame latency, GPU footprint, and what it actually
  takes to run a Primate Vision endpoint at production scale.

We'd rather publish numbers we stand behind than rush a marketing post. If
you're evaluating Primate Vision for a specific use case and you'd like an
early look at the benchmark data for your workload, talk to us.