HWBench

Axelera Metis Edge 130p PCIe card (16GB) vs NVIDIA Jetson Thor T4000

NVIDIA Jetson Thor T4000 is faster in all 3 like-for-like comparisons (largest gap: LLM generation, 12.96×).

Axelera Metis Edge 130p PCIe card (16GB)NVIDIA Jetson Thor T4000
Best LLM generation33.80 tok/s C
2026-10-15 (page last edited)		423 tok/s C
2026-07-21 (page last edited)
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data1 of 71 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

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No published object detection results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 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 Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 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 Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

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No published image classification results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

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No published semantic segmentation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 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 Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson Thor T4000 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.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Thor T400035.00 tok/s
generation_throughput · b=1		Qwen 3 8B
NVFP4 · vLLM · LLM 5–14B		Cunknown power n/a
no power published		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
Axelera Metis Edge 130p PCIe card (16GB)2.70 tok/s
generation_throughput · b=1		qwen3-8b
not stated · Voyager SDK model_axscript.llm · LLM 5–14B		Cunknown power n/a
no power published		Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)
✓ Like-for-like: model-size class LLM ≤4B, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Thor T400095.00 tok/s
generation_throughput · b=1		Qwen3-VL-2B
NVFP4 · vLLM · LLM ≤4B		Cunknown power n/a
no power published		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
Axelera Metis Edge 130p PCIe card (16GB)19.40 tok/s
generation_throughput · b=1		qwen3-0.6b
not stated · Voyager SDK model_axscript.llm · LLM ≤4B		Cunknown power n/a
no power published		Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)
✓ Like-for-like: model-size class unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Thor T400094.00 tok/s
generation_throughput · b=1		Pi 0.5
NVFP4 + FP8 · TRT · unknown		Cunknown power n/a
no power published		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
Axelera Metis Edge 130p PCIe card (16GB)33.80 tok/s
generation_throughput · b=1		lfm2.5-350m
not stated · Voyager SDK model_axscript.llm · unknown		Cunknown power n/a
no power published		Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)
2026-10-15 (page last edited)
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.