AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs Dell Pro Max with GB10

FPGA / Versal coverage note: 1,243 rows come from the AMD Vitis AI 3.0/3.5 Model Zoo tables; 733 (59%) are image classification. Detection, segmentation and other workloads are thinner, and there is no LLM or speech data for these boards. All are vendor-published (grade D). FPGA / Versal overview.

No licensed photo available — placeholder drawing.

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) is faster in the only like-for-like comparison (largest gap: object detection, 27.61×).

	AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	Dell Pro Max with GB10
Best object detection	6100 FPS D Older data (2023)	78.73 FPS A undated
Power	75.00 W spec	n/a
Perf / W	81.34 FPS/W spec	n/a
Price	n/a	n/a
Workloads with data	4 of 7	2 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 unknown, batch unknown (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	2174 FPS E2E throughput, multi thread · b=unknown	pt_face-mask-detection_3.5 INT8 · Vitis AI 3.5 (VART) · unknown	D	75.00 W spec reported in result source — spec	Vitis AI 3.5 Model Zoo performance table Older data (2023)
Dell Pro Max with GB10	78.73 FPS throughput_offline · b=unknown	MLPerf yolo-95 fp4 · CUDA 13.0 · unknown	A	unknown power n/a no power published	MLPerf Inference v6.1 (closed, edge) ID Dell_Pro_Max_GB10x1 undated

instance segmentation

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No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Dell Pro Max with GB10 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	8327 FPS E2E throughput, multi thread · b=unknown	pt_movenet_3.5 INT8 · Vitis AI 3.5 (VART) · unknown	D	75.00 W spec reported in result source — spec	Vitis AI 3.5 Model Zoo performance table Older data (2023)

Dell Pro Max with GB10:

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No published pose estimation results for Dell Pro Max with GB10 or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	7780 FPS E2E throughput, multi thread · b=unknown	pt_OFA-resnet50_0.88_3.5 INT8 · Vitis AI 3.5 (VART) · mid-size CNN	D	75.00 W spec reported in result source — spec	Vitis AI 3.5 Model Zoo performance table Older data (2023)

Dell Pro Max with GB10:

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No published image classification results for Dell Pro Max with GB10 or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published semantic segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	1177 FPS E2E throughput, multi thread · b=unknown	tf2_2D-UNET_3.5 INT8 · Vitis AI 3.5 (VART) · mid-size CNN	D	75.00 W spec reported in result source — spec	Vitis AI 3.5 Model Zoo performance table Older data (2023)

Dell Pro Max with GB10:

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No published semantic segmentation results for Dell Pro Max with GB10 or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Dell Pro Max with GB10 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 Dell Pro Max with GB10 has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Dell Pro Max with GB10	23.92 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	138 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) undated

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML):

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No published LLM generation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Dell Pro Max with GB10 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.