MemryX MX3 M.2 module vs Raspberry Pi 5 (CPU only)
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| MemryX MX3 M.2 module | Raspberry Pi 5 (CPU only) | |
|---|---|---|
| Best object detection | 8519 FPS C 2026-07-15 (published) | 14.92 FPS B 2026-10-03 (page last edited) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 5 of 7 | 4 of 7 |
Best published object detection result per platform. n/a = not published; never estimated.
Show data — all workloads, sources and like-for-like groups
object detection
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 (CPU only) CPU-only | 14.92 FPS inference_time · b=1 | YOLO26n FP32/default · Ultralytics NCNN · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation (benchmark table) 2026-10-03 (page last edited) |
| MemryX MX3 M.2 module MIXED: model-size class unknown vs nano (YOLO-n) | 8519 FPS throughput · b=1 | Malaria-Detector not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
No shared like-for-like group exists for this pair.
instance segmentation
Only MemryX MX3 M.2 module has published instance segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 1023 FPS throughput · b=1 | YOLO26-nano-seg not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
Raspberry Pi 5 (CPU only):
No published instance segmentation results for Raspberry Pi 5 (CPU only) or MemryX MX3 M.2 module 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 MemryX MX3 M.2 module has published pose estimation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 2721 FPS throughput · b=1 | MoveNet.SinglePose.Lightning not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
Raspberry Pi 5 (CPU only):
No published pose estimation results for Raspberry Pi 5 (CPU only) or MemryX MX3 M.2 module 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 (CPU only) CPU-only | 29.59 FPS inference_time · b=1 | YOLO26n-cls FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited) |
| MemryX MX3 M.2 module MIXED: model-size class unknown vs nano (YOLO-n) | 10057 FPS throughput · b=1 | Vehicle-Attributes-recog-barrier-0039 not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
No shared like-for-like group exists for this pair.
semantic segmentation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 (CPU only) CPU-only | 1.20 FPS inference_time · b=1 | YOLO26n-sem FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited) |
| MemryX MX3 M.2 module MIXED: model-size class mobile-class CNN vs nano (YOLO-n) | 2002 FPS throughput · b=1 | MediaPipe-selfie-segmentation-landscape not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
No shared like-for-like group exists for this pair.
speech-to-text
No published speech-to-text results for MemryX MX3 M.2 module 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Raspberry Pi 5 (CPU only) CPU-only | 1.20 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 | C | 13.00 W measured reported in result source — measured | Jeff Geerling ai-benchmarks README (Findings tables) 2026-09-22 (page last edited) |
MemryX MX3 M.2 module:
No published LLM generation results for MemryX MX3 M.2 module 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
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.