AMD Ryzen AI processor (SKU not stated) vs Intel Core Ultra 7 258V (Lunar Lake)
Intel Core Ultra 7 258V (Lunar Lake) is faster in all 2 like-for-like comparisons (largest gap: object detection, 5.73×).
| AMD Ryzen AI processor (SKU not stated) | Intel Core Ultra 7 258V (Lunar Lake) | |
|---|---|---|
| Best object detection | 144 FPS D 2025-12-17 (page last edited) | 300 FPS C 2026-09-27 (page last edited) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 1 of 7 | 2 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Intel Core Ultra 7 258V (Lunar Lake) | 251 FPS inference_time · b=1 | YOLO26s INT8 · Ultralytics + OpenVINO 2026.2.1 · small (YOLO-s) | C | unknown power n/a no power published | Ultralytics documentation: Intel OpenVINO integration benchmark 2026-09-27 (page last edited) |
| AMD Ryzen AI processor (SKU not stated) | 43.76 FPS latency_e2e · b=1 | YOLOv8s-worldv2 A16W8 · ONNX Runtime + Vitis AI EP (Ryzen AI SW), Quark A16W8 AdaRound · small (YOLO-s) | D | unknown power n/a no power published | AMD technical article: Deploying object detection model on AMD AI PC 2026-01-23 (page last edited) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Intel Core Ultra 7 258V (Lunar Lake) | 175 FPS inference_time · b=1 | YOLO26m INT8 · Ultralytics + OpenVINO 2026.2.1 · medium (YOLO-m) | C | unknown power n/a no power published | Ultralytics documentation: Intel OpenVINO integration benchmark 2026-09-27 (page last edited) |
| AMD Ryzen AI processor (SKU not stated) | 48.20 FPS throughput · b=1 | yolov8m XINT8 · Ryzen AI SW (ONNX Runtime, Vitis AI EP) run_inference.py --benchmark · medium (YOLO-m) | D | unknown power n/a no power published | AMD RyzenAI-SW YOLOv8m example (README benchmark table) 2026-08-11 (published) |
instance segmentation
No published instance segmentation results for AMD Ryzen AI processor (SKU not stated) 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
No published pose estimation results for AMD Ryzen AI processor (SKU not stated) 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
No published image classification results for AMD Ryzen AI processor (SKU not stated) 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.
semantic segmentation
No published semantic segmentation results for AMD Ryzen AI processor (SKU not stated) 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
No published speech-to-text results for AMD Ryzen AI processor (SKU not stated) 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| 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 | D | unknown power n/a no power published | OpenVINO official LLM benchmarks (llm_models_7-258V.csv) 2026-10-01 (published) |
AMD Ryzen AI processor (SKU not stated):
No published LLM generation results for AMD Ryzen AI processor (SKU not stated) 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
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.