Intel Core Ultra 7 155H (Meteor Lake) vs Raspberry Pi 5 (CPU only)
Intel Core Ultra 7 155H (Meteor Lake) is faster in the only like-for-like comparison (largest gap: object detection, 11.58×).
| Intel Core Ultra 7 155H (Meteor Lake) | Raspberry Pi 5 (CPU only) | |
|---|---|---|
| Best object detection | 173 FPS C 2026 (year only) | 14.92 FPS B undated |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 1 of 7 | 4 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Intel Core Ultra 7 155H (Meteor Lake) | 173 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics + OpenVINO 2026.2.1 · nano (YOLO-n) | C | unknown power n/a no power published | Ultralytics docs: Intel OpenVINO integration benchmark 2026 (year only) |
| 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 docs benchmark table undated |
instance segmentation
No published instance segmentation results for Intel Core Ultra 7 155H (Meteor Lake) 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.
pose estimation
No published pose estimation results for Intel Core Ultra 7 155H (Meteor Lake) 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.
image classification
Only Raspberry Pi 5 (CPU only) has published image classification results.
| 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 docs: Hailo integration benchmark 2026 (year only) |
Intel Core Ultra 7 155H (Meteor Lake):
No published image classification results for Intel Core Ultra 7 155H (Meteor Lake) 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.
semantic segmentation
Only Raspberry Pi 5 (CPU only) has published semantic segmentation results.
| 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 docs: Hailo integration benchmark 2026 (year only) |
Intel Core Ultra 7 155H (Meteor Lake):
No published semantic segmentation results for Intel Core Ultra 7 155H (Meteor Lake) 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.
speech-to-text
No published speech-to-text results for Intel Core Ultra 7 155H (Meteor Lake) 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) undated |
Intel Core Ultra 7 155H (Meteor Lake):
No published LLM generation results for Intel Core Ultra 7 155H (Meteor Lake) 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.