HWBench

Axelera Metis Edge 130p PCIe card vs Raspberry Pi 5 (CPU only)

Raspberry Pi 5 single-board computer, top view, showing the Broadcom SoC, RAM, USB and Ethernet ports
Raspberry Pi 5. Photo: SimonWaldherr, CC BY 4.0, via Wikimedia Commons.

Axelera Metis Edge 130p PCIe card is faster in all 2 like-for-like comparisons (largest gap: semantic segmentation, 233×).

Axelera Metis Edge 130p PCIe cardRaspberry Pi 5 (CPU only)
Best object detection2894 FPS C
2026-10-15 (page last edited)
14.92 FPS B
2026-10-03 (page last edited)
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data5 of 74 of 7

Best published object detection result per platform (may be from different like-for-like groups — see data). n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Axelera Metis Edge 130p PCIe card1000 FPS
throughput · b=1
YOLOv5n
INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n)
Cunknown power n/a
no power published
Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)
Raspberry Pi 5 (CPU only) CPU-only14.92 FPS
inference_time · b=1
YOLO26n
FP32/default · Ultralytics NCNN · nano (YOLO-n)
Bunknown power n/a
no power published
Ultralytics documentation (benchmark table)
2026-10-03 (page last edited)

instance segmentation

Only Axelera Metis Edge 130p PCIe card has published instance segmentation results.

PlatformResultModel · precision · stackGradePowerSource
Axelera Metis Edge 130p PCIe card287 FPS
throughput · b=1
YOLACT-ResNet50
INT8 · Voyager SDK (GStreamer pipeline) · mid-size CNN
Cunknown power n/a
no power published
Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)

Raspberry Pi 5 (CPU only):

◌

No published instance segmentation results for Raspberry Pi 5 (CPU only) or Axelera Metis Edge 130p PCIe card yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

Only Axelera Metis Edge 130p PCIe card has published pose estimation results.

PlatformResultModel · precision · stackGradePowerSource
Axelera Metis Edge 130p PCIe card762 FPS
throughput · b=1
YOLOv8n-pose
INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n)
Cunknown power n/a
no power published
Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)

Raspberry Pi 5 (CPU only):

◌

No published pose estimation results for Raspberry Pi 5 (CPU only) or Axelera Metis Edge 130p PCIe card yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

⚠ MIXED COMPARISON — not like-for-like. Baseline nano (YOLO-n) at batch 1. Differs: model-size class unknown vs nano (YOLO-n).
PlatformResultModel · precision · stackGradePowerSource
Raspberry Pi 5 (CPU only) CPU-only29.59 FPS
inference_time · b=1
YOLO26n-cls
FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)
Bunknown power n/a
no power published
Ultralytics documentation: Hailo integration benchmark
2026-10-11 (page last edited)
Axelera Metis Edge 130p PCIe card
MIXED: model-size class unknown vs nano (YOLO-n)
6477 FPS
throughput · b=1
SqueezeNet 1.1
INT8 · Voyager SDK (GStreamer pipeline) · unknown
Cunknown power n/a
no power published
Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)

No shared like-for-like group exists for this pair.

semantic segmentation

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Axelera Metis Edge 130p PCIe card280 FPS
throughput · b=1
YOLO26n-sem
INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n)
Cunknown power n/a
no power published
Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)
Raspberry Pi 5 (CPU only) CPU-only1.20 FPS
inference_time · b=1
YOLO26n-sem
FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)
Bunknown power n/a
no power published
Ultralytics documentation: Hailo integration benchmark
2026-10-11 (page last edited)

speech-to-text

◌

No published speech-to-text results for Axelera Metis Edge 130p PCIe card or Raspberry Pi 5 (CPU only) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

Only Raspberry Pi 5 (CPU only) has published LLM generation results.

PlatformResultModel · precision · stackGradePowerSource
Raspberry Pi 5 (CPU only) CPU-only1.20 tok/s
generation_throughput · b=1
DeepSeek R1 14b
as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM 5–14B
C13.00 W measured
reported in result source — measured
Jeff Geerling ai-benchmarks README (Findings tables)
2026-09-22 (page last edited)

Axelera Metis Edge 130p PCIe card:

◌

No published LLM generation results for Axelera Metis Edge 130p PCIe card or Raspberry Pi 5 (CPU only) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

How to read these numbers
Every number is labelled. Confidence: A MLPerf closed, audited · B documented third-party method · C community / review · D vendor-published, not independently verified · E estimate. Power basis: measured with the result · spec vendor spec/envelope · power n/a not published.

Machine-readable: /find.json (see llms.txt); full tables are in “Show data”. Confidence grades: A audited MLPerf closed · B documented third-party · C community · D vendor-published · E estimate. Unknown values are shown as unknown, never estimated. Generated 2026-10-16 from public sources.