HWBenchedge-AI hardware data, cited & graded

Intel Core Ultra 7 258V (Lunar Lake) vs NVIDIA DGX Spark

IntelAI PC · no photo yet
No licensed photo available — placeholder drawing.
NVIDIA DGX Spark desktop AI computer, gold metal-foam chassis, oblique view on a wooden table
NVIDIA DGX Spark. Photo: Daniel Lu (User:dllu), CC BY-SA 4.0, via Wikimedia Commons.

Split result: Intel Core Ultra 7 258V (Lunar Lake) is faster in 2 and NVIDIA DGX Spark in 1 of 3 like-for-like comparisons.

Intel Core Ultra 7 258V (Lunar Lake)NVIDIA DGX Spark
Best object detection300 FPS C
2026 (year only)
990 FPS B
undated
Powern/a153 W spec
Perf / Wn/a6.47 FPS/W spec
Pricen/a$4699 list
Workloads with data2 of 72 of 7

Best published object detection 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

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA DGX Spark990 FPS
inference_time · b=1
YOLO11n
FP16 · Ultralytics TensorRT · nano (YOLO-n)
B153 W spec
platform spec envelope (not measured with this result)
Ultralytics docs benchmark table
undated
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 docs: Intel OpenVINO integration benchmark
2026 (year only)

instance segmentation

◌

No published instance segmentation results for Intel Core Ultra 7 258V (Lunar Lake) 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 Intel Core Ultra 7 258V (Lunar Lake) 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

◌

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

semantic segmentation

◌

No published semantic segmentation results for Intel Core Ultra 7 258V (Lunar Lake) 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 Intel Core Ultra 7 258V (Lunar Lake) 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

✓ Like-for-like: model-size class LLM 5–14B, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)89.29 tok/s
2nd-token throughput, input 32 tokens · b=1
lfm2-8b-a1b
INT4-MIXED · OpenVINO 2026.4.1 GenAI · LLM 5–14B
Dunknown power n/a
no power published
OpenVINO official LLM benchmarks (llm_models_7-258V.csv)
undated
NVIDIA DGX Spark60.39 tok/s
tg128 · b=1
Llama 2 7B
Q4_0 · llama.cpp Vulkan (FA on, commit 657e011) · LLM 5–14B
C153 W spec
platform spec envelope (not measured with this result)
llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API)
2026-10-10
✓ Like-for-like: model-size class unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)200 tok/s
2nd-token throughput, input 32 tokens · b=1
lfm2.5-350m
INT8-CW · OpenVINO 2026.4.1 GenAI · unknown
Dunknown power n/a
no power published
OpenVINO official LLM benchmarks (llm_models_7-258V.csv)
undated
NVIDIA DGX Spark59.60 tok/s
generation_throughput · b=1
Nemotron 3 Nano Omni
NVFP4 · vLLM · unknown
C153 W spec
platform spec envelope (not measured with this result)
NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
undated
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.