Apple M4 (10-core GPU, 120 GB/s) vs NVIDIA GB200 NVL72 (4x NVIDIA GB200)
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Apple M4 (10-core GPU, 120 GB/s) | NVIDIA GB200 NVL72 (4x NVIDIA GB200) | |
|---|---|---|
| Best object detection | 357 FPS B 2026 (year only) | n/a |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 6 of 7 | 1 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
Only Apple M4 (10-core GPU, 120 GB/s) has published object detection results.
| 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 docs: Apple Core AI integration benchmark 2026 (year only) |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published object detection results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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.
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 docs: Apple Core AI integration benchmark 2026 (year only) |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published instance segmentation results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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
Only Apple M4 (10-core GPU, 120 GB/s) has published pose estimation results.
| 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 docs: Apple Core AI integration benchmark 2026 (year only) |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published pose estimation results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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.
image classification
Only Apple M4 (10-core GPU, 120 GB/s) has published image classification results.
| 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 docs: Apple Core AI integration benchmark 2026 (year only) |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published image classification results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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.
semantic segmentation
Only Apple M4 (10-core GPU, 120 GB/s) has published semantic segmentation results.
| 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 docs: Apple Core AI integration benchmark 2026 (year only) |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published semantic segmentation results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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.
speech-to-text
Only NVIDIA GB200 NVL72 (4x NVIDIA GB200) has published speech-to-text results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA GB200 NVL72 (4x NVIDIA GB200) | 22051 FPS throughput_offline · b=unknown | MLPerf whisper fp16 · TensorRT 10.14, CUDA 13.1 · unknown | A | unknown power n/a no power published | MLPerf Inference v6.0 (closed, datacenter) ID 6.0-0041 undated |
Apple M4 (10-core GPU, 120 GB/s):
No published speech-to-text results for Apple M4 (10-core GPU, 120 GB/s) or NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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 |
NVIDIA GB200 NVL72 (4x NVIDIA GB200):
No published LLM generation results for NVIDIA GB200 NVL72 (4x NVIDIA GB200) 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.