NVIDIA and Apple unveil compact AI computers for robots and agents, claiming 2x and 4x generational AI gains

NVIDIA just announced the Jetson Orin Nano 2, a new computer platform for robotics and edge AI that the company says doubles inference performance compared with the Jetson Orin Nano Super. It can also run at 40% less power at equivalent performance. NVIDIA has not yet disclosed pricing, and says the module and developer kit are expected to become available in the first half of 2027.

Compact AI systems are already finding their way into research labs. Duke biomedical engineers, for example, have used the Jetson Orin Nano to control and process images in a compact optical coherence tomography system and to process holographic cytometry data in real time, while researchers developing the Chemist Eye platform use the same hardware for vision-based safety monitoring and robot decision-making in self-driving laboratories.

Meanwhile, Apple, which has emerged as an unlikely beneficiary of the local AI boom, announced a new Mac mini, offered with the M6 or M5 Pro. Preorders opened today, with delivery beginning September 22. The M6 is Apple’s first chip built on a 2 nm process.

In a press release, Apple says the new Mac mini offers “a massive leap in AI performance,” and is designed with “always-on agentic computing” in mind. Specifically, Apple says the M6 Mac mini delivers up to four times faster AI performance than the M4 model, including up to 4.8 times faster LLM prompt processing in LM Studio. M6 configurations have 16GB of unified memory as standard, are configurable to 32GB, and provide up to 170GB/s of memory bandwidth. Whereas Apple originally positioned the Mac mini as an affordable entry point for consumers switching to Mac, and at times went years between major updates, over roughly the past six months the diminutive desktop has gained traction among developers and AI enthusiasts running local models and autonomous agents such as OpenClaw, with Reuters reporting that demand depleted inventories at several Apple stores.

The new Mac mini launch comes amid criticism over delays to its Apple Intelligence features, including a more capable Siri. Apple has agreed to a $250 million settlement over claims that it advertised enhanced Siri and AI capabilities that had yet to arrive.

Apple and NVIDIA are targeting an increasingly crowded and varied market for compact AI computing. NVIDIA also unveiled RTX Spark in May, a Windows platform purpose-built for personal agents. NVIDIA says compact PCs using it will offer up to 128GB of unified memory and up to one petaflop of AI compute, with systems from ASUS, Dell, HP, Lenovo, Microsoft and MSI expected this fall.

NVIDIA’s own DGX Spark, for example, which began shipping in October 2025, is a purpose-built desktop AI system based on the Grace Blackwell GB10 chip. NVIDIA currently sells its 4TB Founders Edition for $4,699, with 128GB of unified memory, 273GB/s of memory bandwidth and up to one petaflop of FP4 AI performance. NVIDIA also offers a two-system bundle, and the systems can be linked over 200 Gb/s ConnectX-7 networking for distributed workloads.

ASUS, Dell, Lenovo and other manufacturers sell systems based on the same GB10 platform, with differences in storage, cooling, support and other system-level features.

Meanwhile, AMD’s Ryzen AI Max platform takes another approach, combining x86 CPUs, integrated Radeon graphics and large pools of shared memory in compact workstations from companies including HP and Framework.

As the table below shows, the compact AI computing landscape spans markedly different use cases, from low-power systems built into robots to deskside machines for developers, researchers and users running local models and autonomous agents. Their performance figures also require some caution: vendors cite a mix of TOPS, FP4 petaflops, memory bandwidth and application-specific benchmarks that are useful within context but cannot be compared directly across systems.

System	Basic positioning	Memory	Claimed AI compute / relevant spec	Current price	Source
NVIDIA Jetson Orin Nano 2	Robotics / edge deployment	8GB	78 TOPS; 2x inference vs. Orin Nano Super, or same performance at 40% less power in 15W mode	Not announced; module and developer kit expected H1 2027	NVIDIA
Apple Mac mini M6	General desktop / local agents	16GB standard; configurable to 32GB	Apple claims up to 4x faster AI vs. M4 Mac mini and 4.8x faster LM Studio prompt processing; 170GB/s	$899+	Apple
Apple Mac mini M5 Pro	Higher-end local AI / dev	Up to 64GB	Apple claims up to 4x faster LM Studio prompt processing vs. M4 Pro; 307GB/s	$1,699+	Apple
NVIDIA RTX Spark PCs	Windows personal agents / local AI	Up to 128GB	Up to 1 PFLOP AI compute	TBD; systems expected fall 2026	NVIDIA
Apple Mac Studio M5 Max	AI/pro workstation	Up to 128GB	Apple claims up to 3.9x faster LLM prompt processing in LM Studio vs. M4 Max; up to 614GB/s	$2,499+	Apple
Apple Mac Studio M5 Ultra	Large local models	Up to 512GB (512GB configuration expected late October 2026)	1.2TB/s memory bandwidth	$5,499+	Apple
NVIDIA DGX Spark	Dedicated desktop AI development	128GB	Up to 1 PFLOP FP4; 273GB/s	$4,699	NVIDIA
ASUS Ascent GX10	DGX Spark-class AI workstation	128GB	1 PFLOP FP4	$4,699	ASUS eShop
Dell Pro Max with GB10	Enterprise local AI workstation	128GB	GB10 Blackwell, 1 PFLOP FP4	Configuration-dependent; verify current listing	Dell
Lenovo ThinkStation PGX	Enterprise AI workstation	128GB	Up to 1 PFLOP FP4 with sparsity; 273GB/s	Varies by storage config; verify current listing	Lenovo Press
Framework Desktop, Ryzen AI Max+ 395	x86/local AI PC	Up to 128GB	Radeon 8060S; 256GB/s	Configuration-dependent; 128GB mainboard $3,149	Framework specs; mainboard

Prices as of Aug. 25, 2026, and subject to change amid ongoing DRAM supply constraints.