Apple M4 (10-core GPU, 120 GB/s) vs NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB)

Apple Mac mini (M4, 2024), small silver aluminium desktop, front view — Apple Mac mini (M4, 2024) — the M4 Pro model shares this enclosure. Photo: Seasider53, CC BY 4.0, via Wikimedia Commons.

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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 DGX B300 (8x NVIDIA B300-SXM-270GB)
Best object detection	357 FPS B 2026-10-01 (page last edited)	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 documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published object detection results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published instance segmentation results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published pose estimation results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published image classification results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 documentation: Apple Core AI integration benchmark 2026-10-01 (page last edited)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published semantic segmentation results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 DGX B300 (8x NVIDIA B300-SXM-270GB) has published speech-to-text results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB)	53267 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 v6.1, closed division, data-centre suite 2026-09-16 (published)

Apple M4 (10-core GPU, 120 GB/s):

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No published speech-to-text results for Apple M4 (10-core GPU, 120 GB/s) or NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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)

NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):

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No published LLM generation results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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.