NVIDIA Jetson AGX Thor vs Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling)
Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) is faster in all 2 like-for-like comparisons (largest gap: LLM generation, 2.73×).
| NVIDIA Jetson AGX Thor | Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | |
|---|---|---|
| Best LLM generation | 523 tok/s C 2026-07-21 (page last edited) | 214 tok/s C 2025-05-06 (page last edited) |
| Power | 130 W Module TDP, Module, max of range 40-130 W | 320 W ● Measured, Whole system |
| Perf / W | 4.02 tok/s/W Module TDP, Module, max of range 40-130 W | 0.669 tok/s/W ● Measured, Whole system |
| Price | $5499 list | n/a |
| Workloads with data | 2 of 7 | 1 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 Thor has published object detection results.
| 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 Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling):
No published object detection results for Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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.
instance segmentation
No published instance segmentation results for NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
semantic segmentation
No published semantic segmentation results for NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 |
|---|---|---|---|---|---|
| Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | 113 tok/s generation_throughput · b=1 | llama3.1:8b Ollama default tag (4-bit unless tag says otherwise) · Ollama (geerlingguy/ollama-benchmark) · LLM 5–14B | C | 471 W ● Measured, Whole system reported in result source — Measured, Whole system | Jeff Geerling ai-benchmarks issue results (comments) 2025-05-06 (page last edited) |
| 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 Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | NVIDIA Jetson Benchmarks on or before 2025-11-08 |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | 214 tok/s generation_throughput · b=1 | deepseek-r1:1.5b Ollama default tag (4-bit unless tag says otherwise) · Ollama (geerlingguy/ollama-benchmark) · LLM ≤4B | C | 320 W ● Measured, Whole system reported in result source — Measured, Whole system | Jeff Geerling ai-benchmarks issue results (comments) 2025-05-06 (page last edited) |
| NVIDIA Jetson AGX Thor | 122 tok/s generation_throughput · b=1 | Qwen3-VL-2B NVFP4 · vLLM · LLM ≤4B | C | 130 W Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited) |
Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) is faster in all 2 like-for-like comparisons (largest gap: LLM generation, 2.73×).
| NVIDIA Jetson AGX Thor | Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | |
|---|---|---|
| Best LLM generation | 523 tok/s C 2026-07-21 (page last edited) | 214 tok/s C 2025-05-06 (page last edited) |
| Power | 130 W Module TDP, Module, max of range 40-130 W | 320 W ● Measured, Whole system |
| Perf / W | 4.02 tok/s/W Module TDP, Module, max of range 40-130 W | 0.669 tok/s/W ● Measured, Whole system |
| Price | $5499 list | n/a |
| Workloads with data | 2 of 7 | 1 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 Thor has published object detection results.
| 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 Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling):
No published object detection results for Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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.
instance segmentation
No published instance segmentation results for NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
semantic segmentation
No published semantic segmentation results for NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 NVIDIA Jetson AGX Thor or Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) 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 |
|---|---|---|---|---|---|
| Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | 113 tok/s generation_throughput · b=1 | llama3.1:8b Ollama default tag (4-bit unless tag says otherwise) · Ollama (geerlingguy/ollama-benchmark) · LLM 5–14B | C | 471 W ● Measured, Whole system reported in result source — Measured, Whole system | Jeff Geerling ai-benchmarks issue results (comments) 2025-05-06 (page last edited) |
| 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 Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | NVIDIA Jetson Benchmarks on or before 2025-11-08 |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Radxa Oryon O6 Mini ITX Board (as tested by Jeff Geerling) | 214 tok/s generation_throughput · b=1 | deepseek-r1:1.5b Ollama default tag (4-bit unless tag says otherwise) · Ollama (geerlingguy/ollama-benchmark) · LLM ≤4B | C | 320 W ● Measured, Whole system reported in result source — Measured, Whole system | Jeff Geerling ai-benchmarks issue results (comments) 2025-05-06 (page last edited) |
| NVIDIA Jetson AGX Thor | 122 tok/s generation_throughput · b=1 | Qwen3-VL-2B NVFP4 · vLLM · LLM ≤4B | C | 130 W Module TDP, Module, max of range 40-130 W reported in result source — Module TDP, Module, max of range 40-130 W | NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited) |
Grades: A audited MLPerf · B third-party · C community · D vendor. How we rank · JSON