APPLE SILICON · SEPTEMBER 2026 INDEX
Pick the unified-memory class.
128 GB unified is the 200k / 1-bit MoE class on this site. A Mac mini is a different download. LocalRig has no first-party Mac filled-200k 27B packet.
128 GB unified
Studio / large unified memory. This is the 128 GB lane from the can-I-run index, on Apple silicon.
- Mac Studio M3 Ultra for Local LLMs: 800GB/s, 256GB, and the Prefill Problem Apple's top inference chip: 800GB/s bandwidth and 256GB unified memory. But the split personality is real—excellent decode throughput on large models, brutal prefill latency that turns long-context work into minutes of waiting. Plus March 2026: the 512GB config is discontinued, capping new Studios at 256GB.
- Mac Studio vs RTX 5090 for Local AI: Unified Memory vs Raw Speed A widely-shared 2026 thread claims the RTX 5090 "can't keep up" with Apple Silicon — and on giant MoE models, it's true: 32GB of VRAM simply can't hold what 128-256GB of unified memory can. But the 5090 crushes anything that fits in its VRAM and owns fine-tuning outright. The real answer is a decision tree by model size, not a winner.
- Mac Studio Clusters over Thunderbolt 5: Trillion-Parameter Models at Home? Four stacked Mac Studios over Thunderbolt 5, running macOS Tahoe RDMA, reportedly unlock trillion-parameter inference at home. A frontier-hobbyist path with honest cost-per-token math, attribution of unverified claims, and clarity on when cloud rental wins.
- How Much Unified Memory Do You Need for Local LLMs? 48GB to 256GB, Mapped to Models A constraint-first guide to Apple Silicon unified memory sizing: the heuristic that maps each memory tier (48/64/128/256GB) to the models it can actually run, and why capacity alone does not guarantee usable speed. Avoids the two costliest Apple mistakes.
Mac mini / smaller
Smaller unified memory. Do not treat a mini as a 128 GB Flash-Next / 0731 box.
- Mac Mini M4 Pro for Local LLMs: The Quiet Entry Point to Apple Inference The Mac Mini M4 Pro with 48GB unified memory is the budget door into local LLM inference: runs 7B–32B models quietly at 30–45W, but unified memory bandwidth limits it to small-to-medium models. A practical guide to sizing, headless setup, and the hard ceiling where larger models hit the wall.
- Mac Mini vs Mac Studio for Local LLMs: Which Should You Actually Buy? The Mac Mini and Mac Studio don't split on speed the way Apple's chip names imply — they split on memory bandwidth and unified memory ceiling. This is the constraint logic: which model sizes the Mini genuinely serves well, where the Studio actually earns its price, and the crossover line between them.
- Best Mac for Local LLM Inference (2026): The Unified-Memory Buying Guide Two specs decide a Mac for local AI — unified memory (what fits) and memory bandwidth (how fast it decodes). The M-series ladder from Mac mini M4 to Mac Studio M3 Ultra, with first-party and community numbers and honest tradeoffs vs a discrete GPU.
M5 configuration
Which M5 Max or M5 Ultra tier to order, and why prompt processing is still slow. M5 tok/s stays empty.
- Mac Studio M5 Max and M5 Ultra for Local LLMs: Which Configuration to Buy M5 Max and M5 Ultra Mac Studio have been on sale since September 22, 2026. This is the configuration guide: which unified-memory tier fits which model class, what Apple's bandwidth and list prices actually are, and when an older M3 Ultra or a non-Mac box is the better buy. M5 tokens per second are not yet measured.
- Why Prompt Processing Is Slow on Apple Silicon (and What Actually Helps) Apple Silicon excels at token generation (decode) but struggles with prompt processing (prefill) on long contexts. The difference between TTFT and tok/s explains why headline throughput hides 10-minute waits, and which optimizations actually work.
Reference
Guides that did not land in a memory-class lane.