AMD Zynq UltraScale+ ZCU104 (ZU7EV) vs Apple M4 (10-core GPU, 120 GB/s)

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | Apple M4 (10-core GPU, 120 GB/s) | |
|---|---|---|
| Best object detection | 463 FPS D Older data (2023) | 357 FPS B 2026-10-01 (page last edited) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 4 of 7 | 6 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 |
|---|---|---|---|---|---|
| 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class unknown vs nano (YOLO-n); batch unknown vs 1 | 463 FPS E2E throughput, multi thread · b=unknown | pt_yolox-nano_coco_416_416_1G INT8 · Vitis AI 3.0 (VART) · unknown | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
No shared like-for-like group exists for this pair.
instance segmentation
Only Apple M4 (10-core GPU, 120 GB/s) has published instance segmentation results.
| 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) |
AMD Zynq UltraScale+ ZCU104 (ZU7EV):
No published instance segmentation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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.
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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1 | 372 FPS E2E throughput, multi thread · b=unknown | pt_movenet_coco_192_192_0.5G INT8 · Vitis AI 3.0 (VART) · mobile-class CNN | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
No shared like-for-like group exists for this pair.
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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1 | 4325 FPS E2E throughput, multi thread · b=unknown | tf_mobilenetv1_0.25_imagenet_128_128_27M INT8 · Vitis AI 3.0 (VART) · mobile-class CNN | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class mid-size CNN vs nano (YOLO-n); batch unknown vs 1 | 352 FPS E2E throughput, multi thread · b=unknown | tf2_2d-unet_nuclei_128_128_5.31G INT8 · Vitis AI 3.0 (VART) · mid-size CNN | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
No shared like-for-like group exists for this pair.
speech-to-text
No published speech-to-text results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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.
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) |
AMD Zynq UltraScale+ ZCU104 (ZU7EV):
No published LLM generation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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.