Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) vs Raspberry Pi 5 + AI HAT+ (Hailo-8)
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) | Raspberry Pi 5 + AI HAT+ (Hailo-8) | |
|---|---|---|
| Best image classification | 182 FPS D undated | 500 FPS B 2026 (year only) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 1 of 7 | 3 of 7 |
Best published image classification result per platform. n/a = not published; never estimated.
Show data — all workloads, sources and like-for-like groups
object detection
Only Raspberry Pi 5 + AI HAT+ (Hailo-8) has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 + AI HAT+ (Hailo-8) | 46.08 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics docs: Hailo integration benchmark 2026 (year only) |
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):
No published object detection results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
instance segmentation
No published instance segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
pose estimation
No published pose estimation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
image classification
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 + AI HAT+ (Hailo-8) | 500 FPS inference_time · b=1 | YOLO26n-cls INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics docs: Hailo integration benchmark 2026 (year only) |
| Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) MIXED: model-size class mid-size CNN vs nano (YOLO-n) | 182 FPS throughput · b=1 | ResNet18 (PyTorch) not stated in table · FPGA AI Suite on-chip parameter streaming; IP throughput · mid-size CNN | D | unknown power n/a no power published | Altera FPGA AI Suite Handbook (performance tables) undated |
No shared like-for-like group exists for this pair.
semantic segmentation
Only Raspberry Pi 5 + AI HAT+ (Hailo-8) has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 + AI HAT+ (Hailo-8) | 28.74 FPS inference_time · b=1 | YOLO26n-sem INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics docs: Hailo integration benchmark 2026 (year only) |
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):
No published semantic segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
speech-to-text
No published speech-to-text results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
LLM generation
No published LLM generation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Raspberry Pi 5 + AI HAT+ (Hailo-8) 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
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.