NVIDIA Jetson Thor T4000 vs Raspberry Pi 5 (CPU only)

No licensed photo available — placeholder drawing.

Raspberry Pi 5 single-board computer, top view, showing the Broadcom SoC, RAM, USB and Ethernet ports — Raspberry Pi 5. Photo: SimonWaldherr, CC BY 4.0, via Wikimedia Commons.

NVIDIA Jetson Thor T4000 is faster in all 2 like-for-like comparisons (largest gap: LLM generation, 29.17×).

	NVIDIA Jetson Thor T4000	Raspberry Pi 5 (CPU only)
Best LLM generation	423 tok/s C undated	4.88 tok/s C undated
Power	n/a	11.90 W measured
Perf / W	n/a	0.410 tok/s/W measured
Price	n/a	n/a
Workloads with data	1 of 7	4 of 7

Best published LLM generation 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

Only Raspberry Pi 5 (CPU only) has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 (CPU only) CPU-only	14.92 FPS inference_time · b=1	YOLO26n FP32/default · Ultralytics NCNN · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics docs benchmark table undated

NVIDIA Jetson Thor T4000:

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No published object detection results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

instance segmentation

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No published instance segmentation results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) 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 Raspberry Pi 5 (CPU only) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 (CPU only) CPU-only	29.59 FPS inference_time · b=1	YOLO26n-cls FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics docs: Hailo integration benchmark 2026 (year only)

NVIDIA Jetson Thor T4000:

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No published image classification results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) 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 Raspberry Pi 5 (CPU only) has published semantic segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 (CPU only) CPU-only	1.20 FPS inference_time · b=1	YOLO26n-sem FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics docs: Hailo integration benchmark 2026 (year only)

NVIDIA Jetson Thor T4000:

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No published semantic segmentation results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) 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

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No published speech-to-text results for NVIDIA Jetson Thor T4000 or Raspberry Pi 5 (CPU only) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

✓ Like-for-like: model-size class LLM 5–14B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson Thor T4000	35.00 tok/s generation_throughput · b=1	Qwen 3 8B NVFP4 · vLLM · LLM 5–14B	C	unknown power n/a no power published	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) undated
Raspberry Pi 5 (CPU only) CPU-only	1.20 tok/s generation_throughput · b=1	DeepSeek R1 14b as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM 5–14B	C	13.00 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) undated

✓ Like-for-like: model-size class LLM ≤4B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson Thor T4000	95.00 tok/s generation_throughput · b=1	Qwen3-VL-2B NVFP4 · vLLM · LLM ≤4B	C	unknown power n/a no power published	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) undated
Raspberry Pi 5 (CPU only) CPU-only	4.88 tok/s generation_throughput · b=1	Llama 3.2:3b as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM ≤4B	C	11.90 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) undated

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.