AMD Ryzen AI Max+ (Strix Halo) iGPU: edge AI benchmarks
Key results
| Workload | Best result | Model · precision | Power · perf/W | Grade · date | Source |
|---|---|---|---|---|---|
| LLM generation | 54.38 tok/s batch 1 | Llama 2 7B Q4_0 · llama.cpp Vulkan (FA on, commit fb4b273) | 120 W (spec) 0.453 tok/s/W | C 2026-10-10 (page last edited) | llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API) |
| LLM prefill | 1704 tok/s batch 1 | Llama 2 7B Q4_0 · llama.cpp Vulkan (FA on, commit fb4b273) | 120 W (spec) 14.20 tok/s/W | C 2026-10-10 (page last edited) | llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API) |
Best published result per workload, across model sizes. For like-for-like groups, open the per-workload tables below.
Show data — per-workload tables
object detection
No published object detection results for AMD Ryzen AI Max+ (Strix Halo) iGPU 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 AMD Ryzen AI Max+ (Strix Halo) iGPU 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 Max+ (Strix Halo) iGPU 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 Max+ (Strix Halo) iGPU 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 Max+ (Strix Halo) iGPU 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 Max+ (Strix Halo) iGPU 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 group | Best result | Model · precision · stack | Grade | Power | Source · date | Rank in group |
|---|---|---|---|---|---|---|
| LLM 5–14B · b=1 | 54.38 tok/s | Llama 2 7B Q4_0 · llama.cpp Vulkan (FA on, commit fb4b273) | C | 120 W spec | llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API) 2026-10-10 (page last edited) | 17 of 54 |
LLM prefill
| Like-for-like group | Best result | Model · precision · stack | Grade | Power | Source · date | Rank in group |
|---|---|---|---|---|---|---|
| LLM 5–14B · b=1 | 1704 tok/s | Llama 2 7B Q4_0 · llama.cpp Vulkan (FA on, commit fb4b273) | C | 120 W spec | llama.cpp discussion #10879 Vulkan scoreboard (via GitHub API) 2026-10-10 (page last edited) | 4 of 19 |
Compare with another platform (107)
8xMI355X_2xEPYC_9575F (8x AMD Instinct MI355X 288GB HBM3e) · AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) · AMD Kria KV260 Vision AI Starter Kit (K26 SOM) · AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) · AMD Ryzen AI processor (SKU not stated) · AMD Versal AI Core VCK190 (VC1902) · AMD Versal AI Edge Series Gen 2 VEK385 · AMD Versal AI Edge VEK280 (VE2802) · AMD Zynq UltraScale+ ZCU102 (ZU9EG) · AMD Zynq UltraScale+ ZCU104 (ZU7EV) · Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) · Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) · Apple M4 (10-core GPU, 120 GB/s) · Apple Mac mini M4 Pro 64GB · Axelera Metis Edge 130p PCIe card · Axelera Metis Edge 130p PCIe card (16GB) · Axelera Metis Embedded 113m M.2 card · Cisco UCS C880A M8 (8x NVIDIA B300-SXM-270GB) · Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) · CoreWeave GB200 NVL72 (4x NVIDIA GB200) · CoreWeave GB300 NVL72 (4x NVIDIA GB300) · Dell Pro Max with GB10 · G8825Z5 (8x AMD Instinct MI350X 288GB HBM3e) · G894-AD3-AAX7 (8x NVIDIA B300-SXM-270GB) · G894-SD3-AAX7 (8x NVIDIA B300-SXM-270GB) · G894-ZD3-AAX7 (8x NVIDIA B300-SXM-270GB) · Google Coral Dev Board (Edge TPU) · Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 · HPE ProLiant Compute DL380a Gen12 (10x NVIDIA RTX PRO 6000 Blackwell Server Edition) · HPE ProLiant Compute DL380a Gen12 (8x NVIDIA RTX PRO 6000 Blackwell Server Edition) · HPE ProLiant Compute XD685 (8x AMD Instinct MI355X 288GB HBM3e) · HPE ProLiant DL385 Gen11 (4x NVIDIA RTX PRO 6000 Blackwell Server Edition) · Hailo-10H (M.2/PCIe, x86 host) · Hailo-8 (M.2/PCIe, x86 host) · Hailo-8L (M.2/PCIe, x86 host) · Intel Arc A-Series Graphics · Intel Arc B-Series Graphics · Intel Atom X6425E · Intel Atom x7425E · Intel Celeron 6305E · Intel Core 5 330 · Intel Core Ultra 7 155H · Intel Core Ultra 7 155H (Meteor Lake) · Intel Core Ultra 7 255H · Intel Core Ultra 7 258V (Lunar Lake) · Intel Core Ultra 7 265H · Intel Core Ultra 7 368H · Intel Core Ultra 9 288V · Intel Core Ultra X7 358H (Panther Lake) · Intel Core i5-1235U · Intel Core i5-1335U · Intel Core i5-13600K · Intel Core i7-1185G7 · Intel Core i7-1185GRE · Intel Core i7-12700H · Intel Core i7-1355U · Intel Data Center GPU Flex 170 · Intel N100 · Intel Xeon Gold 5218T · Intel Xeon Gold 6154 desktop (CPU only, TFLite) · Intel Xeon Gold 6338N · Intel Xeon Platinum 6972P · Intel Xeon Platinum 8280 · Intel Xeon Platinum 8380 · Intel Xeon Platinum 8480+ · Intel Xeon Platinum 8580 · Lattice Avant-E Evaluation Board (sensAI) · Lattice CertusPro-NX Voice and Vision ML Board (sensAI) · Lattice CrossLink-NX-33 Voice and Vision ML Board (sensAI) · Lattice iCE40 UltraPlus Mobile Development Platform (sensAI) · MemryX MX3 M.2 module · Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) · NDP9120 (N/A) · NUCLEO-L4R5ZI (STM32L4R5ZIT6U) · NUCLEO-U575ZI-Q (STM32U575ZIT6Q) · NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) · NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) · NVIDIA DGX Spark · NVIDIA GB200 NVL72 (4x NVIDIA GB200) · NVIDIA GB300 NVL72 (4x NVIDIA GB300) · NVIDIA Jetson AGX Orin 64GB · NVIDIA Jetson AGX Thor · NVIDIA Jetson Orin NX 16GB · NVIDIA Jetson Orin Nano Super · NVIDIA Jetson Thor T4000 · Nebius B300 n1 (8x NVIDIA B300-SXM-270GB) · Nebius GB300 NVL72 (4x NVIDIA GB300) · Qualcomm Dragonwing IQ-9075 EVK · Qualcomm Dragonwing RB3 Gen 2 (QCS6490) · Qualcomm Snapdragon X Elite (CRD) · Qualcomm Snapdragon X2 Elite (CRD) · QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) · Raspberry Pi 5 (CPU only) · Raspberry Pi 5 + AI HAT+ (Hailo-8) · Rockchip RK1808 (NPU) · Rockchip RK3562 (NPU) · Rockchip RK3566/RK3568 (NPU) · Rockchip RK3576 (NPU, single core of 2) · Rockchip RK3588 (NPU, single core of 3) · Rockchip RV1109 (NPU) · Rockchip RV1126 (NPU) · Rockchip RV1126B (NPU) · TI AM68A (8 TOPS) · TRIGKEY Mini PC (AMD Ryzen 5 5560U, CPU) · Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) · XA NB3I-E12 (8x NVIDIA B300-SXM-270GB) · XE7745_8xMI350P_2xEPYC_9455 (8x AMD Instinct MI350P)
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.