Apple M4 (10-core GPU, 120 GB/s) vs Axelera Metis Embedded 113m M.2 card
Axelera Metis Embedded 113m M.2 card is faster in all 4 like-for-like comparisons (largest gap: semantic segmentation, 5.50×).
| Apple M4 (10-core GPU, 120 GB/s) | Axelera Metis Embedded 113m M.2 card | |
|---|---|---|
| Best object detection | 357 FPS B 2026-10-01 (page last edited) | 3004 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Embedded 113m M.2 card | 824 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Embedded 113m M.2 card | 536 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Embedded 113m M.2 card | 746 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
| 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 Embedded 113m M.2 card MIXED: model-size class unknown vs nano (YOLO-n) | 5881 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Axelera Metis Embedded 113m M.2 card | 294 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
No published speech-to-text results for Apple M4 (10-core GPU, 120 GB/s) or Axelera Metis Embedded 113m M.2 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 Embedded 113m M.2 card:
No published LLM generation results for Axelera Metis Embedded 113m M.2 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
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.