HWBench

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) vs Intel Core Ultra 7 258V (Lunar Lake)

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)Intel Core Ultra 7 258V (Lunar Lake)
Best image classification182 FPS D
2026-08-10 (published)
n/a
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data1 of 72 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 Intel Core Ultra 7 258V (Lunar Lake) has published object detection results.

PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)300 FPS
inference_time · b=1
YOLO26n
FP32 · Ultralytics + OpenVINO 2026.2.1 · nano (YOLO-n)
Cunknown power n/a
no power published
Ultralytics documentation: Intel OpenVINO integration benchmark
2026-09-27 (page last edited)

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):

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No published object detection results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Intel Core Ultra 7 258V (Lunar Lake) 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Intel Core Ultra 7 258V (Lunar Lake) 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Intel Core Ultra 7 258V (Lunar Lake) 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.

PlatformResultModel · precision · stackGradePowerSource
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
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)

Intel Core Ultra 7 258V (Lunar Lake):

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No published image classification results for Intel Core Ultra 7 258V (Lunar Lake) 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

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No published semantic segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Intel Core Ultra 7 258V (Lunar Lake) 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 Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) or Intel Core Ultra 7 258V (Lunar Lake) 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 Intel Core Ultra 7 258V (Lunar Lake) has published LLM generation results.

PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)135 tok/s
2nd-token throughput, input 32 tokens · b=1
minicpm4-0.5b
INT4-MIXED · OpenVINO 2026.4.1 GenAI · LLM ≤4B
Dunknown power n/a
no power published
OpenVINO official LLM benchmarks (llm_models_7-258V.csv)
2026-10-01 (published)

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 Intel Core Ultra 7 258V (Lunar Lake) 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
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.