Apple M4 (10-core GPU, 120 GB/s) vs Axelera Metis Edge 130p PCIe card
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Axelera Metis Edge 130p PCIe card is faster in all 4 like-for-like comparisons (largest gap: semantic segmentation, 5.24×).
| Apple M4 (10-core GPU, 120 GB/s) | Axelera Metis Edge 130p PCIe card | |
|---|---|---|
| Best object detection | 357 FPS B 2026-10-01 (page last edited) | 2894 FPS C 2026-10-15 (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
✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Edge 130p PCIe card | 1000 FPS throughput · b=1 | YOLOv5n INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n) | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| 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) |
instance segmentation
✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Edge 130p PCIe card | 574 FPS throughput · b=1 | YOLO11n-seg INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n) | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| 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) |
pose estimation
✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Edge 130p PCIe card | 762 FPS throughput · b=1 | YOLOv8n-pose INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n) | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| 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) |
image classification
⚠ MIXED COMPARISON — not like-for-like. Baseline nano (YOLO-n) at batch 1. Differs: model-size class unknown vs nano (YOLO-n).
| 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) |
| Axelera Metis Edge 130p PCIe card MIXED: model-size class unknown vs nano (YOLO-n) | 6477 FPS throughput · b=1 | SqueezeNet 1.1 INT8 · Voyager SDK (GStreamer pipeline) · unknown | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
No shared like-for-like group exists for this pair.
semantic segmentation
✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Edge 130p PCIe card | 280 FPS throughput · b=1 | YOLO26n-sem INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n) | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| 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) |
speech-to-text
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No published speech-to-text results for Apple M4 (10-core GPU, 120 GB/s) or Axelera Metis Edge 130p PCIe card 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) |
Axelera Metis Edge 130p PCIe card:
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No published LLM generation results for Axelera Metis Edge 130p PCIe card 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.