Apple M4 (10-core GPU, 120 GB/s) vs Rockchip RK3562 (NPU)
Apple M4 (10-core GPU, 120 GB/s) is faster in all 3 like-for-like comparisons (largest gap: pose estimation, 11.43×).
| Apple M4 (10-core GPU, 120 GB/s) | Rockchip RK3562 (NPU) | |
|---|---|---|
| Best object detection | 357 FPS B 2026-10-01 (page last edited) | 57.30 FPS C 2026-10-13 (page last edited) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 6 of 7 | 5 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 |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 357 FPS latency_e2e · b=1 | YOLO26n FP16 · Ultralytics 8.4.168 Core AI (coreai-torch 0.4.3), macOS 27.0 · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited) |
| Rockchip RK3562 (NPU) | 57.30 FPS throughput · b=1 | yolov6n INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n) | C | unknown power n/a no power published | Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited) |
instance segmentation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 196 FPS latency_e2e · b=1 | YOLO26n-seg FP16 · Ultralytics 8.4.168 Core AI (coreai-torch 0.4.3), macOS 27.0 · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited) |
| Rockchip RK3562 (NPU) | 40.30 FPS throughput · b=1 | yolov5n-seg INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n) | C | unknown power n/a no power published | Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited) |
pose estimation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 370 FPS latency_e2e · b=1 | YOLO26n-pose FP16 · Ultralytics 8.4.168 Core AI (coreai-torch 0.4.3), macOS 27.0 · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited) |
| Rockchip RK3562 (NPU) | 32.40 FPS throughput · b=1 | yolov8n-pose INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n) | C | unknown power n/a no power published | Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited) |
image classification
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 417 FPS latency_e2e · b=1 | YOLO26n-cls FP16 · Ultralytics 8.4.168 Core AI (coreai-torch 0.4.3), macOS 27.0 · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited) |
| Rockchip RK3562 (NPU) MIXED: model-size class mobile-class CNN vs nano (YOLO-n) | 289 FPS throughput · b=1 | mobilenetv2-12 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN | C | unknown power n/a no power published | Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited) |
No shared like-for-like group exists for this pair.
semantic segmentation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 53.48 FPS latency_e2e · b=1 | YOLO26n-sem FP16 · Ultralytics 8.4.168 Core AI (coreai-torch 0.4.3), macOS 27.0 · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited) |
| Rockchip RK3562 (NPU) MIXED: model-size class mobile-class CNN vs nano (YOLO-n) | 21.00 FPS throughput · b=1 | deeplab-v3-plus-mobilenet-v2 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN | C | unknown power n/a no power published | Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited) |
No shared like-for-like group exists for this pair.
speech-to-text
No published speech-to-text results for Apple M4 (10-core GPU, 120 GB/s) or Rockchip RK3562 (NPU) 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 Apple M4 (10-core GPU, 120 GB/s) has published LLM generation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Apple M4 (10-core GPU, 120 GB/s) | 24.11 tok/s tg128 · b=1 | Llama 2 7B Q4_0 · llama.cpp Metal (commit 8e672ef) · LLM 5–14B | C | unknown power n/a no power published | llama.cpp discussion #4167 scoreboard (via GitHub API) 2026-10-01 (page last edited) |
Rockchip RK3562 (NPU):
No published LLM generation results for Rockchip RK3562 (NPU) or Apple M4 (10-core GPU, 120 GB/s) 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.