HWBench

Apple M4 (10-core GPU, 120 GB/s) vs Rockchip RV1126B (NPU)

Apple Mac mini (M4, 2024), small silver aluminium desktop, front view
Apple Mac mini (M4, 2024) — the M4 Pro model shares this enclosure. Photo: Seasider53, CC BY 4.0, via Wikimedia Commons.

Apple M4 (10-core GPU, 120 GB/s) is faster in all 3 like-for-like comparisons (largest gap: pose estimation, 6.27×).

Apple M4 (10-core GPU, 120 GB/s)Rockchip RV1126B (NPU)
Best object detection357 FPS B
2026-10-01 (page last edited)
106 FPS C
2026-10-13 (page last edited)
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data6 of 75 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
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)
Bunknown power n/a
no power published
Ultralytics documentation: Apple Core AI integration benchmark
2026-10-01 (page last edited)
Rockchip RV1126B (NPU)106 FPS
throughput · b=1
yolov5n
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

instance segmentation

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
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)
Bunknown power n/a
no power published
Ultralytics documentation: Apple Core AI integration benchmark
2026-10-01 (page last edited)
Rockchip RV1126B (NPU)83.80 FPS
throughput · b=1
yolov5n-seg
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

pose estimation

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
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)
Bunknown power n/a
no power published
Ultralytics documentation: Apple Core AI integration benchmark
2026-10-01 (page last edited)
Rockchip RV1126B (NPU)59.10 FPS
throughput · b=1
yolov8n-pose
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

image classification

⚠ MIXED COMPARISON — not like-for-like. Baseline nano (YOLO-n) at batch 1. Differs: model-size class mobile-class CNN vs nano (YOLO-n).
PlatformResultModel · precision · stackGradePowerSource
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)
Bunknown power n/a
no power published
Ultralytics documentation: Apple Core AI integration benchmark
2026-10-01 (page last edited)
Rockchip RV1126B (NPU)
MIXED: model-size class mobile-class CNN vs nano (YOLO-n)
374 FPS
throughput · b=1
mobilenetv2-12
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN
Cunknown 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

⚠ MIXED COMPARISON — not like-for-like. Baseline nano (YOLO-n) at batch 1. Differs: model-size class mobile-class CNN vs nano (YOLO-n).
PlatformResultModel · precision · stackGradePowerSource
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)
Bunknown power n/a
no power published
Ultralytics documentation: Apple Core AI integration benchmark
2026-10-01 (page last edited)
Rockchip RV1126B (NPU)
MIXED: model-size class mobile-class CNN vs nano (YOLO-n)
30.90 FPS
throughput · b=1
deeplab-v3-plus-mobilenet-v2
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN
Cunknown 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 RV1126B (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.

PlatformResultModel · precision · stackGradePowerSource
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
Cunknown power n/a
no power published
llama.cpp discussion #4167 scoreboard (via GitHub API)
2026-10-01 (page last edited)

Rockchip RV1126B (NPU):

◌

No published LLM generation results for Rockchip RV1126B (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
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.