PlbKin190/physical-ai-atlas-data huggingface dataset:
NVIDIA Jetson AGX Thor (T5000) — GPU module by NVIDIA (US)
AI performance: 2070 TFLOPS FP4 (sparse, Blackwell GPU)
Power (W): 130
Memory: 128 GB LPDDR5X
Price (USD): 3499
Form factor: System-on-module (Jetson T5000) + developer kit; 40-130 W envelope
Availability: GA since August 2025 (dev kit $3,499; production modules shipping)
Target applications: humanoid, AMR, manipulation, healthcare, agriculture, vision
Robots using it: Boston Dynamics Atlas, Agility Robotics Digit, Figure, Amazon Robotics, Unitree H2 Plus, Caterpillar, 1X (evaluating)
Notable: The de facto flagship compute for humanoid robots in 2026: 7.5x the AI compute of Orin, 128 GB of memory to run VLA models on-robot, adopted or evaluated by nearly every major humanoid maker including Boston Dynamics, Agility, Figure and OpenAI.
À noter : Le calculateur de référence des robots humanoïdes en 2026 : 7,5x la puissance IA d'Orin, 128 Go de mémoire pour exécuter des modèles VLA embarqués, adopté ou évalué par la quasi-totalité des acteurs majeurs (Boston Dynamics, Agility, Figure, OpenAI).
NVIDIA Jetson AGX Orin — GPU module by NVIDIA (US)
AI performance: 275 TOPS INT8 (sparse; 138 TOPS dense)
Power (W): 60
Memory: 64 GB LPDDR5 (unified)
Price (USD): 1999
Form factor: System-on-module + developer kit; 15-60 W configurable
Availability: GA since 2022; the installed-base reference for embedded robotics AI
Target applications: humanoid, AMR, drone, vision, industrial
Robots using it: Unitree G1 EDU (Orin NX), Skydio X10, NVIDIA Isaac GR00T reference platforms
Notable: Four years after launch, Orin remains the workhorse of the robotics industry, powering everything from Unitree humanoids to Skydio drones; Thor supersedes it at the high end but Orin keeps the volume and the mature Isaac/ROS ecosystem.
À noter : Quatre ans après son lancement, Orin reste le cheval de trait de la robotique, des humanoïdes Unitree aux drones Skydio ; Thor le remplace sur le haut de gamme mais Orin conserve le volume et l'écosystème Isaac/ROS le plus mature.
Qualcomm Dragonwing IQ-9075 (IQ9 Series) — SoC by Qualcomm (US)
AI performance: 100 TOPS dense / 200 TOPS sparse (INT8, Hexagon NPU)
Memory: 36 GB LPDDR5 (EVK configuration)
Form factor: SoC; EVK, SMARC modules and robot controllers from Lantronix, Advantech, Tria
Availability: EVK and modules available (2025-2026); flagship Dragonwing IQ-10 for humanoids in early access June 2026, global availability targeted September 2026
Target applications: humanoid, AMR, industrial, drone, vision
Robots using it: Figure (partnership announced CES 2026), Booster Robotics (partner), KUKA Robotics (partner)
Notable: Qualcomm's frontal assault on NVIDIA Jetson: a full robotics stack unveiled at CES 2026, from household robots to full-size humanoids, with Figure and KUKA among named partners and a power-efficiency pitch inherited from mobile.
À noter : L'assaut frontal de Qualcomm contre NVIDIA Jetson : une pile robotique complète dévoilée au CES 2026, du robot domestique à l'humanoïde grandeur nature, avec Figure et KUKA parmi les partenaires annoncés et un argument d'efficacité énergétique hérité du mobile.
Hailo-10H — accelerator by Hailo (IL)
AI performance: 40 TOPS INT4 / 20 TOPS INT8
Power (W): 2.5
Memory: On-module DRAM via direct DDR interface (M.2 2242/2280 module)
Form factor: Discrete accelerator chip; M.2 Key M module
Availability: GA since July 2025; automotive grade (AEC-Q100) with 2026 start of production
Target applications: drone, vision, AMR, automotive, edge GenAI
Robots using it: Raspberry Pi AI HAT+ 2 (dev platform), HP and Fujitsu edge products (integrations)
Notable: First market-available discrete edge accelerator to run LLMs and VLMs fully on-device at ~2.5 W typical, positioning Israel's Hailo as the low-power counterweight to Jetson for drones and vision robotics.
À noter : Premier accélérateur discret du marché à exécuter LLM et VLM entièrement en local pour ~2,5 W typiques, positionnant l'israélien Hailo comme le contrepoids basse consommation de Jetson pour les drones et la robotique de vision.
Axelera AI Metis AIPU — accelerator by Axelera AI (NL)
AI performance: 214 TOPS INT8 (peak, quad-core AIPU; 15 TOPS/W)
Power (W): 8
Memory: 1 GB DRAM (M.2 card); 4-16 GB (PCIe card)
Price (USD): 149
Form factor: M.2 2280 M-Key card (3.5-9 W typ.) and PCIe HHHL card (8-15 W typ.)
Availability: Shipping (M.2/PCIe via distribution); next-gen Europa AIPU (629 TOPS INT8) shipments from H1 2026
Target applications: vision, AMR, industrial, retail analytics
Notable: Europe's best-funded edge-AI chip startup (Eindhoven, NL): digital in-memory computing on RISC-V delivering 214 TOPS for ~$149, with the 629-TOPS Europa AIPU and a EUR 61.6M EuroHPC grant anchoring Europe's inference-sovereignty push.
À noter : La startup européenne de puces edge-IA la mieux financée (Eindhoven, Pays-Bas) : calcul en mémoire numérique sur RISC-V offrant 214 TOPS pour ~149 $, avec l'AIPU Europa à 629 TOPS et une subvention EuroHPC de 61,6 M EUR à l'appui de la souveraineté européenne de l'inférence.
Tesla FSD Computer AI4 (HW4) — in-house chip by Tesla (US)
AI performance: Not officially disclosed; third-party estimates ≈100–150 TOPS INT8 for the dual‑SoC AI4 system
Memory: GDDR6 (~384 GB/s per third-party analyses); AI4+ variant announced 2026 with doubled memory (32 GB per SoC)
Form factor: Dual-SoC redundant compute board shared between vehicles and Optimus
Availability: In production (Tesla vehicles and Optimus); successor AI5 taped out, engineering samples expected late 2026, volume 2027
Target applications: humanoid, automotive
Robots using it: Tesla Optimus
Notable: The only humanoid brain built fully in-house at automotive scale: the same AI4 computer runs Tesla cars and Optimus, and Musk calls the 8x-faster AI5 'absolutely critical' for Optimus, admitting AI4 is not enough for the humanoid program.
À noter : Le seul cerveau d'humanoïde conçu entièrement en interne à l'échelle automobile : le même calculateur AI4 équipe les voitures Tesla et Optimus, et Musk qualifie l'AI5 (8x plus rapide) d'« absolument critique » pour Optimus, reconnaissant qu'AI4 ne suffit pas au programme humanoïde.
SiMa.ai MLSoC Modalix — SoC by SiMa.ai (US)
AI performance: 50 TOPS (machine learning accelerator; multi-modal GenAI + CNN)
Power (W): 10
Memory: 8-32 GB LPDDR5 (SoM variants)
Price (USD): 349
Form factor: SoC + pin-compatible SoM (8 GB $349 / 32 GB $599); DevKit $1,499
Availability: In production since August 2025 (sampling since January 2025)
Target applications: vision, AMR, industrial, defense, healthcare
Notable: One of the first chips marketed explicitly as 'Physical AI' silicon: runs LLMs, VLMs and classic computer vision on one SoC under 10 W, targeting robotics and industrial edge as a low-power alternative to Jetson.
À noter : L'une des premières puces commercialisées explicitement comme silicium « Physical AI » : exécute LLM, VLM et vision classique sur un seul SoC sous 10 W, visant la robotique et l'edge industriel en alternative basse consommation à Jetson.
D-Robotics RDK S100 (Horizon Robotics group) — SoC by D-Robotics (Horizon Robotics spin-off) (CN)
AI performance: 80 TOPS (S100) / 128 TOPS (S100P) BPU (INT8-equivalent)
Memory: 12 GB LPDDR5 (96-bit)
Form factor: Single-SoC computation-control board: 6x Cortex-A78AE + BPU + real-time MCU cores for motion control
Availability: GA in China since 2025; international push at Embedded World 2026 (street price ~$389-549 via distributors)
Target applications: humanoid, quadruped, AMR, manipulation, vision
Robots using it: Unitree G1 (launch demo), Leju Robotics humanoids, LimX Dynamics
Notable: China's main domestic alternative to Jetson for robot builders: the first single-SoC kit merging AI perception and real-time motion control, already adopted by 20+ embodied-AI companies including Leju and LimX Dynamics.
À noter : La principale alternative domestique chinoise à Jetson pour les roboticiens : premier kit mono-SoC fusionnant perception IA et contrôle moteur temps réel, déjà adopté par plus de 20 entreprises d'IA incarnée dont Leju et LimX Dynamics.
Kalray K300 (MPPA3-80 Coolidge2) — accelerator by Kalray (FR)
AI performance: 40 TOPS INT8 / 20 TFLOPS FP16 (K300 card, 80-core MPPA3-80 v2)
Memory: 16 GB DDR4 @ 3200 MT/s
Form factor: PCIe Gen4 card with 4x 10/25G SFP28; 80-core VLIW manycore DPU
Availability: Shipping; company refocused on semiconductors in 2025 after divesting its data-acceleration platform to DataCore
Target applications: vision, industrial, defense, edge AI
Notable: France's manycore pioneer survived a 2025 liquidity crisis by refocusing on its MPPA/DPU silicon (semiconductor revenue nearly quadrupled to EUR 14.3M); with GrAI Matter Labs absorbed by Snap, Kalray is one of the last French embedded-AI processor players.
À noter : Le pionnier français du manycore a survécu à une crise de liquidité en 2025 en se recentrant sur son silicium MPPA/DPU (chiffre d'affaires semi-conducteurs presque quadruplé à 14,3 M EUR) ; après l'absorption de GrAI Matter Labs par Snap, Kalray reste l'un des derniers acteurs français du processeur d'IA embarquée.
Rockchip RK3588 — SoC by Rockchip (CN)
AI performance: 6 TOPS (3-core NPU; ~2 TOPS/core; supports INT4/INT8/INT16/BF16/TF32; optimized for INT8)
Memory: External LPDDR4/4x/LPDDR5 (board-dependent)
Form factor: SoC (8x Cortex-A76/A55 + Mali-G610); ubiquitous on SBCs, SMARC and robot control boards; -40 to +85 C industrial variants
Availability: GA since 2022; massive installed base across robot controllers and SBCs
Target applications: AMR, vision, education robots, industrial
Robots using it: Theobroma Systems JAGUAR mobile-robot computer, Dusun IoT AGV/AMR controllers
Notable: The budget workhorse of physical AI: its modest 6-TOPS NPU plus strong CPU/GPU make it the default brain of countless AMRs, robot dev boards and Chinese robotics products where a Jetson would be overkill.
À noter : Le cheval de trait économique de l'IA physique : son NPU modeste de 6 TOPS allié à un CPU/GPU solide en fait le cerveau par défaut d'innombrables AMR, cartes robotiques et produits chinois là où un Jetson serait surdimensionné.