Axelera Metis Edge 130p PCIe card (16GB) vs NVIDIA Jetson AGX Orin 64GB

NVIDIA Jetson AGX Orin 64GB is faster in all 3 like-for-like comparisons (largest gap: LLM generation, 11.11×).
| Axelera Metis Edge 130p PCIe card (16GB) | NVIDIA Jetson AGX Orin 64GB | |
|---|---|---|
| Best LLM generation | 33.80 tok/s C 2026-10-15 (page last edited) | 273 tok/s C 2026-07-21 (page last edited) |
| Power | n/a | 65.00 W spec |
| Perf / W | n/a | 4.20 tok/s/W spec |
| Price | n/a | $3499 list |
| Workloads with data | 1 of 7 | 3 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 NVIDIA Jetson AGX Orin 64GB has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 435 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | 65.00 W spec platform spec envelope (not measured with this result) | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
Axelera Metis Edge 130p PCIe card (16GB):
No published object detection results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
instance segmentation
No published instance segmentation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
pose estimation
No published pose estimation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
image classification
No published image classification results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 104 FPS throughput · b=1 | SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown | C | 65.00 W spec platform spec envelope (not measured with this result) | arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published) |
Axelera Metis Edge 130p PCIe card (16GB):
No published semantic segmentation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB 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
No published speech-to-text results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
LLM generation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 30.00 tok/s generation_throughput · b=1 | Qwen 3 8B W4A16 · vLLM · LLM 5–14B | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 60.00 tok/s generation_throughput · b=1 | Qwen3-VL-2B W4A16 · vLLM · LLM ≤4B | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 44.00 tok/s generation_throughput · b=1 | Cosmos3 Edge (Reasoner) BF16 · vLLM · unknown | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
NVIDIA Jetson AGX Orin 64GB is faster in all 3 like-for-like comparisons (largest gap: LLM generation, 11.11×).
| Axelera Metis Edge 130p PCIe card (16GB) | NVIDIA Jetson AGX Orin 64GB | |
|---|---|---|
| Best LLM generation | 33.80 tok/s C 2026-10-15 (page last edited) | 273 tok/s C 2026-07-21 (page last edited) |
| Power | n/a | 65.00 W spec |
| Perf / W | n/a | 4.20 tok/s/W spec |
| Price | n/a | $3499 list |
| Workloads with data | 1 of 7 | 5 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 NVIDIA Jetson AGX Orin 64GB has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 435 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | 65.00 W spec platform spec envelope (not measured with this result) | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
Axelera Metis Edge 130p PCIe card (16GB):
No published object detection results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
instance segmentation
No published instance segmentation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
pose estimation
No published pose estimation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published image classification results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 6424 FPS throughput_offline · b=unknown | MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN | D | 65.00 W spec platform spec envelope (not measured with this result) | NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023) |
Axelera Metis Edge 130p PCIe card (16GB):
No published image classification results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 104 FPS throughput · b=1 | SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown | C | 65.00 W spec platform spec envelope (not measured with this result) | arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published) |
Axelera Metis Edge 130p PCIe card (16GB):
No published semantic segmentation results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB 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 Jetson AGX Orin 64GB has published speech-to-text results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 1170 FPS throughput_offline · b=unknown | MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T | D | 65.00 W spec platform spec envelope (not measured with this result) | NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023) |
Axelera Metis Edge 130p PCIe card (16GB):
No published speech-to-text results for Axelera Metis Edge 130p PCIe card (16GB) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
LLM generation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 30.00 tok/s generation_throughput · b=1 | Qwen 3 8B W4A16 · vLLM · LLM 5–14B | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 60.00 tok/s generation_throughput · b=1 | Qwen3-VL-2B W4A16 · vLLM · LLM ≤4B | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown power n/a no power published | Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Orin 64GB | 44.00 tok/s generation_throughput · b=1 | Cosmos3 Edge (Reasoner) BF16 · vLLM · unknown | C | 65.00 W spec platform spec envelope (not measured with this result) | 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 | C | unknown 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
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.