Nvidia RTX 5060 Ti · yolov9-t 320

Frigate docs reference

Checked 2026-10-19· Frigate docs hardware page ·db-073

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

Inference

5 ms

docs reference

Est. capacity

~200 det/s

1000 ÷ 5 ms · estimate

Cameras

—

not reported

CPU

—

not reported

Power

—

not reported

Parts

prices show only once verified by hand

Accelerator

Nvidia RTX 5060 Ti

ONNX (Nvidia / GPU) · 4 builds on DetectFPS

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

ONNX (Nvidia / GPU)

Detector instances

—

Model, as reported

yolov9-t 320

Model family · input

yolov9-t · 320

Camera resolution

—

Cameras

—

Frigate version

—

Numbers

dashes mean the source didn't say

Inference

5 ms

Inference range

—

Total fps

—

CPU

—

Power

—

Used in stats

Yes

Source

Where

docs.frigate.video/frigate/hardware

Date, as the source wrote it

—

Added to DetectFPS

copied from the Frigate project's hardware page on 2026-10-19; approximate reference value

What this build implies

~200 detections per second

1000 ÷ 5 ms. No camera count was reported, so use the calculator to see what that covers: at 5 fps and Typical activity, that is about 48 cameras comfortably.

Open in the calculator

Hardware

Nvidia RTX 5060 Ti

Detector type

ONNX (Nvidia / GPU)

Builds on DetectFPS

Median, this model

5 ms (1 build)

Price

price not tracked yet

Shown because this guide lists Nvidia RTX 5060 Ti in its hardware (hardware_ids). Cross-device guides are only linked when they name this device or its host.

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Frigate docs

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Cameras—

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checked 2026-10-19Frigate docs

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Cameras—

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Aug 2025GitHub #19741

Intel N97 (iGPU)

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Speed18.5 ms

Cameras8

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OpenVINO (Intel)

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Cameras—

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Host—
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3 other builds use the same device; the rest share the yolov9-t model family.