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Apple Neural Engine (M4)

Reference target for on-device foundation-model workloads; benchmarks via Core ML.

top models on this chip

Object detection

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Object detection
#ModelQuantLatency p50ThroughputAcc.Power
1YOLO27-EdgeFP1619.1 ms52 FPS99.9%7.1 W
2RT-DETR-EdgeFP1619.6 ms51 FPS99.8%6.8 W
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Depth

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Depth
#ModelQuantLatency p50ThroughputAcc.Power
1MiDaS-Distilled-SFP1615.9 ms63 FPS99.4%7.4 W
2ZoeDepth-MobileFP1622.7 ms44 FPS99.5%6.4 W
3Depth-Anything-EdgeMIXED29.2 ms34 FPS98.7%6.9 W
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Segmentation

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Segmentation
#ModelQuantLatency p50ThroughputAcc.Power
1Mask2Former-MobileFP1636.3 ms28 FPS99.6%7.3 W
2SAM-3-DistilledFP1655.9 ms18 FPS99.5%7.7 W
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Embedded ASR

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Embedded ASR
#ModelQuantLatency p50ThroughputAcc.Power
1Whisper-Edge-TinyINT8203.5 ms31 tok/s97.7%6.8 W
2Distil-Whisper-TinyFP16333.5 ms19 tok/s99.8%7.3 W
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Multimodal

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Multimodal
#ModelQuantLatency p50ThroughputAcc.Power
1MobileCLIP-S2FP1634.9 ms29 FPS99.6%6.5 W
2MobileCLIP-BFP1666.9 ms15 FPS99.9%6.6 W
3Florence-2-EdgeFP1670.2 ms14 FPS99.8%7.2 W
4DINO-v3-DistilledFP1678.1 ms13 FPS99.8%7.1 W
5SmolVLM-3BMIXED342.2 ms2.9 FPS99.4%7.3 W
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Pose

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
Pose
#ModelQuantLatency p50ThroughputAcc.Power
1MoveNet-LightningINT84.65 ms215 FPS98.2%7.1 W
2MediaPipe-Hands-EdgeINT85.29 ms189 FPS97.6%6.2 W
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OCR

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Sorted by latency p50 · matched-pair runs on Apple Neural Engine (M4)
OCR
#ModelQuantLatency p50ThroughputAcc.Power
1PaddleOCR-Edge-v5FP1610.2 ms98 FPS99.4%7.2 W
2DocLayout-EdgeFP1616.6 ms60 FPS99.7%6.6 W