Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) vs NVIDIA DGX Spark
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) | NVIDIA DGX Spark | |
|---|---|---|
| Best image classification | 182 FPS D undated | n/a |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | $4699 list |
| Workloads with data | 1 of 7 | 2 of 7 |
Best published image classification result per platform. n/a = not published; never estimated.
Show data — all workloads, sources and like-for-like groups
object detection
Only NVIDIA DGX Spark has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA DGX Spark | 990 FPS inference_time · b=1 | YOLO11n FP16 · Ultralytics TensorRT · nano (YOLO-n) | B | 153 W spec platform spec envelope (not measured with this result) | Ultralytics docs benchmark table undated |
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):
No published object detection results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) has published image classification results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) | 182 FPS throughput · b=1 | ResNet18 (PyTorch) not stated in table · FPGA AI Suite on-chip parameter streaming; IP throughput · mid-size CNN | D | unknown power n/a no power published | Altera FPGA AI Suite Handbook (performance tables) undated |
NVIDIA DGX Spark:
No published image classification results for NVIDIA DGX Spark or Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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 DGX Spark has published LLM generation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA DGX Spark | 60.39 tok/s tg128 · b=1 | Llama 2 7B Q4_0 · llama.cpp Vulkan (FA on, commit 657e011) · LLM 5–14B | C | 153 W spec platform spec envelope (not measured with this result) | llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API) 2026-10-10 |
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):
No published LLM generation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or NVIDIA DGX Spark 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.