HWBench

Intel Core Ultra 7 258V (Lunar Lake) vs NVIDIA Jetson AGX Orin 64GB

NVIDIA Jetson AGX Orin developer kit with its retail box, on a black background
NVIDIA Jetson AGX Orin developer kit. Photo: Auledas, CC BY 4.0, via Wikimedia Commons.
Showing the newest results per platform and source. 12 superseded older results are hidden.Showing all results, including 12 superseded by newer results from the same source.

Split result: Intel Core Ultra 7 258V (Lunar Lake) is faster in 4 and NVIDIA Jetson AGX Orin 64GB in 2 of 6 like-for-like comparisons.

Intel Core Ultra 7 258V (Lunar Lake)NVIDIA Jetson AGX Orin 64GB
Best object detection300 FPS C
2026-09-27 (page last edited)		435 FPS B
2026-10-13 (page last edited)
Powern/a65.00 W spec
Perf / Wn/a6.69 FPS/W spec
Pricen/a$3499 list
Workloads with data2 of 73 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 Jetson AGX Orin 64GB435 FPS
inference_time · b=1		YOLO26n
INT8 · Ultralytics TensorRT · nano (YOLO-n)		B65.00 W spec
platform spec envelope (not measured with this result)		Ultralytics documentation (benchmark table)
2026-10-13 (page last edited)
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)
✓ Like-for-like: model-size class small (YOLO-s), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)251 FPS
inference_time · b=1		YOLO26s
INT8 · Ultralytics + OpenVINO 2026.2.1 · small (YOLO-s)		Cunknown power n/a
no power published		Ultralytics documentation: Intel OpenVINO integration benchmark
2026-09-27 (page last edited)
NVIDIA Jetson AGX Orin 64GB80.90 FPS
throughput · b=1		YOLO11s (640x640)
INT8 · TensorRT (ONNX export) · small (YOLO-s)		C65.00 W spec
platform spec envelope (not measured with this result)		arXiv 2608.00927 AgriJetsonBench (abstract figures)
2026-08-02 (published)

instance segmentation

◌

No published instance segmentation results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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 Jetson AGX Orin 64GB 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 Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published semantic segmentation results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB104 FPS
throughput · b=1		SegFormer-B0 (640x640)
FP16 · TensorRT (ONNX export) · unknown		C65.00 W spec
platform spec envelope (not measured with this result)		arXiv 2608.00927 AgriJetsonBench (abstract figures)
2026-08-02 (published)

Intel Core Ultra 7 258V (Lunar Lake):

◌

No published semantic segmentation results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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 Jetson AGX Orin 64GB 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 ≤4B, batch 1. Model, precision and stack may still differ.
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)
NVIDIA Jetson AGX Orin 64GB60.00 tok/s
generation_throughput · b=1		Qwen3-VL-2B
W4A16 · vLLM · LLM ≤4B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
✓ 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)
2026-10-01 (published)
NVIDIA Jetson AGX Orin 64GB30.00 tok/s
generation_throughput · b=1		Qwen 3 8B
W4A16 · vLLM · LLM 5–14B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
✓ Like-for-like: model-size class LLM 15–40B, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB55.00 tok/s
generation_throughput · b=1		Qwen3-30B-A3B
W4A16 · vLLM · LLM 15–40B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
Intel Core Ultra 7 258V (Lunar Lake)53.48 tok/s
2nd-token throughput, input 1024 tokens · b=1		lfm2-24b-a2b
INT4-MIXED · OpenVINO 2026.4.1 GenAI · LLM 15–40B		Dunknown power n/a
no power published		OpenVINO official LLM benchmarks (llm_models_7-258V.csv)
2026-10-01 (published)
✓ 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)
2026-10-01 (published)
NVIDIA Jetson AGX Orin 64GB44.00 tok/s
generation_throughput · b=1		Cosmos3 Edge (Reasoner)
BF16 · vLLM · unknown		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)

Split result: Intel Core Ultra 7 258V (Lunar Lake) is faster in 4 and NVIDIA Jetson AGX Orin 64GB in 2 of 6 like-for-like comparisons.

Intel Core Ultra 7 258V (Lunar Lake)NVIDIA Jetson AGX Orin 64GB
Best object detection300 FPS C
2026-09-27 (page last edited)		435 FPS B
2026-10-13 (page last edited)
Powern/a65.00 W spec
Perf / Wn/a6.69 FPS/W spec
Pricen/a$3499 list
Workloads with data2 of 75 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 Jetson AGX Orin 64GB435 FPS
inference_time · b=1		YOLO26n
INT8 · Ultralytics TensorRT · nano (YOLO-n)		B65.00 W spec
platform spec envelope (not measured with this result)		Ultralytics documentation (benchmark table)
2026-10-13 (page last edited)
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)
✓ Like-for-like: model-size class small (YOLO-s), batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Intel Core Ultra 7 258V (Lunar Lake)251 FPS
inference_time · b=1		YOLO26s
INT8 · Ultralytics + OpenVINO 2026.2.1 · small (YOLO-s)		Cunknown power n/a
no power published		Ultralytics documentation: Intel OpenVINO integration benchmark
2026-09-27 (page last edited)
NVIDIA Jetson AGX Orin 64GB80.90 FPS
throughput · b=1		YOLO11s (640x640)
INT8 · TensorRT (ONNX export) · small (YOLO-s)		C65.00 W spec
platform spec envelope (not measured with this result)		arXiv 2608.00927 AgriJetsonBench (abstract figures)
2026-08-02 (published)

instance segmentation

◌

No published instance segmentation results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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 Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published image classification results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB6424 FPS
throughput_offline · b=unknown		MLPerf ResNet
INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN		D65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson Benchmarks (MLPerf v3.1 results table)
Older data (2023)

Intel Core Ultra 7 258V (Lunar Lake):

◌

No published image classification results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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 NVIDIA Jetson AGX Orin 64GB has published semantic segmentation results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB104 FPS
throughput · b=1		SegFormer-B0 (640x640)
FP16 · TensorRT (ONNX export) · unknown		C65.00 W spec
platform spec envelope (not measured with this result)		arXiv 2608.00927 AgriJetsonBench (abstract figures)
2026-08-02 (published)

Intel Core Ultra 7 258V (Lunar Lake):

◌

No published semantic segmentation results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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

Only NVIDIA Jetson AGX Orin 64GB has published speech-to-text results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB1170 FPS
throughput_offline · b=unknown		MLPerf RNN-T
INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T		D65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson Benchmarks (MLPerf v3.1 results table)
Older data (2023)

Intel Core Ultra 7 258V (Lunar Lake):

◌

No published speech-to-text results for Intel Core Ultra 7 258V (Lunar Lake) or NVIDIA Jetson AGX Orin 64GB 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 ≤4B, batch 1. Model, precision and stack may still differ.
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)
NVIDIA Jetson AGX Orin 64GB60.00 tok/s
generation_throughput · b=1		Qwen3-VL-2B
W4A16 · vLLM · LLM ≤4B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
✓ 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)
2026-10-01 (published)
NVIDIA Jetson AGX Orin 64GB30.00 tok/s
generation_throughput · b=1		Qwen 3 8B
W4A16 · vLLM · LLM 5–14B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
✓ Like-for-like: model-size class LLM 15–40B, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Orin 64GB55.00 tok/s
generation_throughput · b=1		Qwen3-30B-A3B
W4A16 · vLLM · LLM 15–40B		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
Intel Core Ultra 7 258V (Lunar Lake)53.48 tok/s
2nd-token throughput, input 1024 tokens · b=1		lfm2-24b-a2b
INT4-MIXED · OpenVINO 2026.4.1 GenAI · LLM 15–40B		Dunknown power n/a
no power published		OpenVINO official LLM benchmarks (llm_models_7-258V.csv)
2026-10-01 (published)
✓ 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)
2026-10-01 (published)
NVIDIA Jetson AGX Orin 64GB44.00 tok/s
generation_throughput · b=1		Cosmos3 Edge (Reasoner)
BF16 · vLLM · unknown		C65.00 W spec
platform spec envelope (not measured with this result)		NVIDIA Jetson AI Lab benchmarks (benchmarks.json)
2026-07-21 (page last edited)
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.