MemryX MX3 M.2 module vs NVIDIA Jetson AGX Thor
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| MemryX MX3 M.2 module | NVIDIA Jetson AGX Thor | |
|---|---|---|
| Best object detection | 8519 FPS C 2026-07-15 (published) | 719 FPS B 2026-10-13 (page last edited) |
| Power | n/a | 130 W spec |
| Perf / W | n/a | 5.53 FPS/W spec |
| Price | n/a | $5499 list |
| Workloads with data | 5 of 7 | 2 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Thor | 719 FPS inference_time · b=1 | YOLO26n FP16 · Ultralytics TensorRT · nano (YOLO-n) | B | 130 W spec platform spec envelope (not measured with this result) | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
| MemryX MX3 M.2 module MIXED: model-size class unknown vs nano (YOLO-n) | 8519 FPS throughput · b=1 | Malaria-Detector not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
No shared like-for-like group exists for this pair.
instance segmentation
Only MemryX MX3 M.2 module has published instance segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 1023 FPS throughput · b=1 | YOLO26-nano-seg not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
NVIDIA Jetson AGX Thor:
No published instance segmentation results for NVIDIA Jetson AGX Thor or MemryX MX3 M.2 module 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 MemryX MX3 M.2 module has published pose estimation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 2721 FPS throughput · b=1 | MoveNet.SinglePose.Lightning not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
NVIDIA Jetson AGX Thor:
No published pose estimation results for NVIDIA Jetson AGX Thor or MemryX MX3 M.2 module 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 MemryX MX3 M.2 module has published image classification results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 2317 FPS throughput · b=1 | ResNet-50 (MXA-Optimized) not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
NVIDIA Jetson AGX Thor:
No published image classification results for NVIDIA Jetson AGX Thor or MemryX MX3 M.2 module 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 MemryX MX3 M.2 module has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| MemryX MX3 M.2 module | 1998 FPS throughput · b=1 | Deeplab-v3 not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN | C | unknown power n/a no power published | MemryX Model Explorer (SDK 2.2) 2026-07-15 (published) |
NVIDIA Jetson AGX Thor:
No published semantic segmentation results for NVIDIA Jetson AGX Thor or MemryX MX3 M.2 module 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 MemryX MX3 M.2 module or NVIDIA Jetson AGX Thor 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 NVIDIA Jetson AGX Thor has published LLM generation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson AGX Thor | 41.32 tok/s tok/s gen, concurrency 1 · b=1 | Deepseek R1 7B n/s on page · NVIDIA (vLLM/TensorRT-LLM per page) · LLM 5–14B | D | 130 W spec platform spec envelope (not measured with this result) | NVIDIA Jetson Benchmarks on or before 2025-11-08 |
MemryX MX3 M.2 module:
No published LLM generation results for MemryX MX3 M.2 module or NVIDIA Jetson AGX Thor 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
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.