Nvidia RTX 3060 · yolov7-320

Frigate 0.15.2Community build older version, may be outdated

Posted Aug 2025·GitHub #19741 ·db-138

I run this too, add my numbers Opens the submit form prefilled with this hardware, model and version

Inference

5–7 ms

as reported

Est. capacity

~167 det/s

1000 ÷ 6 ms · estimate

Cameras

—

not reported

CPU

—

not reported

Power

—

not reported

Parts

prices show only once verified by hand

Accelerator

Nvidia RTX 3060

ONNX (Nvidia / GPU), TensorRT (Nvidia, legacy) · 4 builds on DetectFPS · reported as “Nvidia RTX 3060 12GB”

price not tracked yet

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Host

—

not reported

—

CPU

—

not reported

—

Cameras

—

resolution not reported

—

Tracked totalno verified prices yet

Setup

Detector

TensorRT (Nvidia, legacy)

Detector instances

—

Model, as reported

yolov7-320

Model family · input

yolov7 · 320

Camera resolution

—

Cameras

—

Frigate version

0.15.2 (0.15 series, 3 behind newest)

—

Numbers

dashes mean the source didn't say

Inference

—

Inference range

5–7 ms

Total fps

—

CPU

—

Power

—

Used in stats

Yes

Notes and flags

This build ran Frigate 0.15.2, more than two minor versions behind 0.18.2. Detectors and models have changed since, so treat the number as historical.

Source

Where

github.com/blakeblackshear/frigate/discussions/19741

Date, as the source wrote it

2025-08 (month precision)

Added to DetectFPS

from a public post; numbers copied as written, not re-tested

What this build implies

~167 detections per second

1000 ÷ 6 ms. No camera count was reported, so use the calculator to see what that covers: at 5 fps and Typical activity, that is about 39 cameras comfortably.

Open in the calculator

Hardware

Nvidia RTX 3060

Detector type

ONNX (Nvidia / GPU), TensorRT (Nvidia, legacy)

Builds on DetectFPS

Median, this model

6 ms (1 build)

Price

price not tracked yet

Shown because this guide lists Nvidia RTX 3060 in its hardware (hardware_ids). Cross-device guides are only linked when they name this device or its host.

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