| Model & Quantization | VRAM Demand | AMD Ryzen AI Max+ 395 Strix Halo | Apple Mac Studio M5 Ultra |
|---|---|---|---|
| OpenAI gpt-oss 120B (Q4_K_M, 8k) | 71.2 GB | Runs Comfortably (~35 tok/s) | Runs Comfortably (~115 tok/s) |
| Meta LLaMA 3.3 70B (Q8_0, 8k) | 81.7 GB | Fits GTT (~2.6 tok/s Slow) | Runs Comfortably (~12 tok/s) |
| Meta LLaMA 3.3 70B (Q4_K_M, 8k) | 46.1 GB | Fits GTT (~4.8 tok/s) | Runs Comfortably (~22 tok/s) |
| GLM-4.5-Air 106B (Q4_K_M, 8k) | 65.9 GB | Runs Comfortably (~21 tok/s) | Runs Comfortably (~68 tok/s) |
| Alibaba Qwen3 235B-A22B (Q3_K_M, 8k) | 109.3 GB | Tight w/ gttsize=112640 | Tight w/ sysctl wired_limit |
Comparing Ryzen AI Max+ 395 ('Strix Halo') against Apple's M5 Ultra showcases why bus width governs 100B+ unified rigs. AMD pairs two 8-core Zen 5 CCDs with a 40-CU RDNA 3.5 `Radeon 8060S` (`gfx1151`) iGPU and a 50-TOPS XDNA 2 NPU, but ties the entire 128GB LPDDR5X-8000 pool to a 256-bit controller capping peak transfer at 256 GB/s. That makes Strix Halo responsive strictly on ultra-sparse MoEs (`gpt-oss 120B`, 5.1B active at ~35 tok/s) while dense 70B models crawl under 5 tok/s. Apple bridges two M5 Max dies via its silicon UltraFusion interposer, multiplying bus width to 1024-bit (1,024–1,200 GB/s) alongside per-core GPU Neural Accelerators. Consequently, M5 Ultra streams dense 70B Q4/Q8 models and `Qwen3 235B-A22B` 4x–4.7x faster via MLX, reserving Strix Halo mainly for x86 Linux/Docker purists.
On Linux Strix Halo, add `amdgpu.gttsize=112640 ttm.pages_limit=28835840` inside `/etc/default/grub` so ROCm and Vulkan claim 110GB dynamically without rigid BIOS UMA carve-outs, and run sparse `gpt-oss 120B` instead of dense 70B. On Mac Studio M5 Ultra, execute `sudo sysctl iogpu.wired_limit_mb=112640` to unlock 110GB wired RAM for 128k contexts.
Matched Upgrade: Pairing a Mac Studio M5 Ultra or Strix Halo desktop with an OWC Express 1M2 40Gbps USB4 enclosure bypasses pricey soldered internal SSD upgrades while feeding massive 106B–235B GGUF and MLX weights at 3,150+ MB/s.
OWC 40Gbps USB4 NVMe on Amazon Prime ↗Zero monthly subscriptions, 100% private inference, and unmetered tokens for your homelab or workstation.
Skip the upfront hardware expense. Spin up secure cloud instances from $0.35/hr on Vast.ai or $0.79/hr on RunPod.
LLM token generation reads every active parameter from memory per token step. M5 Ultra's 1024-bit UltraFusion interface pushes 1,024–1,200 GB/s versus 256 GB/s on Strix Halo's 256-bit bus, delivering 4x+ decoding throughput across 70B and 120B weights.
Pick Strix Halo ($2,200–$3,300) when your workflow strictly requires native x86_64 Ubuntu Linux, compact PCIe-free ROCm Docker containers, full Vulkan compatibility, or dual-boot Windows PC flexibility—and plan your local agent stack around ultra-sparse `gpt-oss 120B` rather than slow dense 70B checkpoints.
Inspect exact KV-cache formulas, test 32k/128k context allocations, or compare cloud rental break-even costs in the interactive matchmaker.
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