crtdrops
REAL-HARDWARE VERIFICATION · SAMPLE REPORT

YOLO26n · FP32

yolo26n.onnx · graph identity f21c7ca23a529ada… · measured on 3 October 2026

Download this report as PDF — it is exactly what a client receives.

The verdict

It runs on all 3 configurations measured, with correct results. The fastest: Intel N100 · ONNX Runtime, at 57.6 ms per inference, about 17 per second.

Raspberry Pi 5 · ONNX Runtime
Runs
126.4 ms
per inference, p50 · p95 134.4 ms · 8 per second
Intel N100 · ONNX Runtime
Runs
57.6 ms
per inference, p50 · p95 58.9 ms · 17 per second
Intel N100 · OpenVINO
Runs
64.0 ms
per inference, p50 · p95 65.6 ms · 16 per second

Performance

Model inference, in milliseconds. “End to end” adds preparing the input and processing the output.

CONFIGURATION P50 P95 P99 END TO END P50 PER SECOND
Raspberry Pi 5 · 8 GB · ONNX Runtime 1.30.0126.4134.4138.3138.18
Intel N100 · 8 GB · ONNX Runtime 1.30.057.658.959.367.217
Intel N100 · 8 GB · OpenVINO 2026.4.064.065.671.372.416

Correct results

Outputs are compared with a reference computed with ONNX Runtime on a reference machine, with the same inputs.

What was expected and what happened

Before measuring, the protocol writes down what it expects in each dimension. Then it is checked against what was measured.

DIMENSION RASPBERRY PI 5 · ONNX RUNTIME INTEL N100 · ONNX RUNTIME INTEL N100 · OPENVINO
Valid ONNX model✓ passesonnx.checker OK✓ passesonnx.checker OK—
Runtime load✓ passesload 57.68 ms✓ passesload 116.609 ms✓ passesload 359.373 ms
Operator support✓ passessession created with no rejected operators✓ passessession created with no rejected operators—
Fits in memory✓ passespeak RSS = 3.0% of RAM✓ passespeak RSS = 3.3% of RAM✓ passespeak RSS = 3.5% of RAM
Correct results✓ passesrecall 100% · precision 100% vs reference✓ passesrecall 100% · precision 100% vs reference✓ passesrecall 100% · precision 100% vs reference
p95 ≤ 200 ms◆ meets itp95 134.3902 ms vs ≤ 200 ms◆ meets itp95 58.8727 ms vs ≤ 200 ms◆ meets itp95 65.5797 ms vs ≤ 200 ms
Thermal stability◆ passesTmax 65.3 °C——
CPU support——✓ passesfully executed on CPU
Faster than ONNX Runtime——◆ nop50 64.045 ms vs 57.5655 ms in C08 (-11.3%)

✓ the expectation was confirmed · ◆ it was unknown and is now measured · · not evaluated in this measurement

14 predictions confirmed, none wrong.

Not evaluated in this measurement: export.

Memory, load and temperature

RASPBERRY PI 5 · ONNX RUNTIME INTEL N100 · ONNX RUNTIME INTEL N100 · OPENVINO
Model load58 ms117 ms359 ms
Peak memory239 MB · 3.0% of RAM255 MB · 3.3% of RAM265 MB · 3.5% of RAM
Temperature57 → 65 °C53 → 62 °C54 → 64 °C
CPU frequency2400–2400 MHz2816–2900 MHz2821–3150 MHz
Thermal throttlingnono, by frequency (no direct reading)no, by frequency (no direct reading)

The model

File
yolo26n.onnx · 9.5 MB · FP32
Source
Ultralytics yolo26n.pt (official; never a third-party conversion)
License
AGPL-3.0
Inputs
images FLOAT [1, 3, 640, 640]
Outputs
output0 FLOAT [1, 300, 6]
Graph
ONNX opset 17 · 384 nodes · 23 operator types
File identity
843640bc7ae797dfbf3d9828ced4bfce393a78949b6ed282a0db874f64ef2680
Graph identity
f21c7ca23a529adaf73a497aba4b366aa0d94f9f5bdf02c55aebbbe1460bd90f

Measurement conditions

RASPBERRY PI 5 · ONNX RUNTIME INTEL N100 · ONNX RUNTIME INTEL N100 · OPENVINO
SystemDebian GNU/Linux 13 (trixie)Ubuntu 24.04.5 LTSUbuntu 24.04.5 LTS
Python3.13.53.12.33.12.3
Effective precisionFP32, the model's ownFP32, the model's ownf32, pinned and verified
Threadsruntime defaultsruntime defaultsruntime defaults
Measurements100 after 20 warm-up runs100 after 20 warm-up runs100 after 20 warm-up runs
Before measuringdevice freshly rebooteddevice freshly rebooteddevice freshly rebooted
Frozen environmentENV-T1-RPI5-8GB-LAB01-v01ENV-T2-N100-8GB-LAB01-v02ENV-T2-N100-8GB-LAB01-v02
ObservationOBS-C07-20261003T215041Z-b5c74fOBS-C08-20261003T224756Z-1c9208OBS-C09-20261003T224811Z-9534d9

What this report does not cover


This is a sample report. The model is the official Ultralytics YOLO26n, which is public, and that is why this report can be published. Client reports are confidential, and the model is deleted when they are delivered.

Generated on 5 October 2026.