GoKawiilOur local AI explorations in 2026 have so far focused on two main platforms: Nvidia’s GB10, as seen in the DGX Spark and Dell Pro Max with GB10, and AMD’s Ryzen AI Max+ 395, aka Strix Halo, as seen in the Corsair AI Workstation 300 and the Ryzen AI Halo. We’ve generally favored GB10 systems for these kinds of local AI development sandboxes. Their solid all-around performance and broad AI software compatibility make them easy to love, even if raw LLM inference throughput isn’t that high.
But Apple’s Mac Studio is another compelling option for local AI trailblazers who want systems with large unified memory pools, powerful GPUs, and high memory bandwidth to enable faster tokens-per-second throughput than either GB10 or Strix Halo can provide. And until someone builds another unified memory SoC with a memory bus as wide as what Apple uses for its Max and Ultra chips, Apple Silicon is, in fact, the only game in town for more memory bandwidth from a chip of this design.
Why focus so much on memory bandwidth for local LLM performance to begin with? To keep it very short, the decode phase of LLM inference is virtually always sequential. Every output token (starting with the first one generated as part of the prefill process) has to be run through every layer in a model in order to generate the next token, and so all the active model weights in a layer have to be streamed to the GPU from its memory as the token makes its way through each one.
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Because the amount of computation required for each individual token at each layer is tiny, the speed of the entire decode process basically becomes dependent on how fast those model weights can be streamed in from GPU memory. That makes systems with large memory pools (for holding large models) and high memory bandwidth (for streaming those model weights to the GPU) appealing, and Apple Silicon is the only platform that lets you have both characteristics at a (relatively) reasonable cost.
Apple’s last Mac Studio refresh was in March 2025 and marked the introduction of two versions of the system. The higher-end version uses the M3 Ultra SoC with 819GB/s of memory bandwidth across both the 28-CPU-core, 60-GPU-core mode and the 32-CPU-core, 80-GPU-core model.
The M4 Max version of the Mac Studio encompasses two versions with greater divergence in specs than just core counts. The base M4 Max includes a 14-core CPU (10 performance cores and four efficiency cores) with 410GB/s of memory bandwidth, and it can be upgraded to a 16-core CPU (12 performance cores and four efficiency cores) with 546GB/s of memory bandwidth.
We reviewed both of these systems at launch, but Apple generously lent us another M4 Max with the 16-core CPU, 40-core GPU, and 128GB of memory for LLM-specific tests. At the time, the price of that system was $3,699 or so, close to the DGX Spark’s $3,999 list price.
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But as the RAMpocalypse has rolled on, the Mac Studio has become more limited in its configuration options and harder to find in stock. The M4 Max version we tested now tops out at 64GB of RAM, and lead times for that system are over two months out. Regardless, it’s the most comparable system that Apple has for the DGX Spark and GB10 platform more generally, at least back when dollar-for-dollar meant something in this market.
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