{"generatedAt":"2026-10-22T08:51:51.131Z","sourcesUpdatedAt":"2026-10-22T08:41:13.166Z","site":"https://hardware.branolabs.com","fxNote":"priceEurApprox uses fixed approximate FX rates","skus":[{"id":"rtx-5090","slug":"rtx-5090","name":"NVIDIA GeForce RTX 5090 32GB","brand":"NVIDIA","category":"gpu","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Top consumer card for local LLMs; street price far above MSRP in 2026.","url":"https://hardware.branolabs.com/sku/rtx-5090"},{"id":"rtx-5080","slug":"rtx-5080","name":"NVIDIA GeForce RTX 5080 16GB","brand":"NVIDIA","category":"gpu","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Strong 16GB Blackwell for 14B–32B models.","url":"https://hardware.branolabs.com/sku/rtx-5080"},{"id":"rtx-4090","slug":"rtx-4090","name":"NVIDIA GeForce RTX 4090 24GB","brand":"NVIDIA","category":"gpu","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Still a local-AI workhorse; used market active.","url":"https://hardware.branolabs.com/sku/rtx-4090"},{"id":"rtx-3090","slug":"rtx-3090","name":"NVIDIA GeForce RTX 3090 24GB","brand":"NVIDIA","category":"gpu","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Best used $/VRAM for many hobbyists; dual-3090 common.","url":"https://hardware.branolabs.com/sku/rtx-3090"},{"id":"rtx-3090-ti","slug":"rtx-3090-ti","name":"NVIDIA GeForce RTX 3090 Ti 24GB","brand":"NVIDIA","category":"gpu","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Used Ampère flagship; similar AI role to 3090.","url":"https://hardware.branolabs.com/sku/rtx-3090-ti"},{"id":"rtx-4080-super","slug":"rtx-4080-super","name":"NVIDIA GeForce RTX 4080 Super 16GB","brand":"NVIDIA","category":"gpu","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"16GB Ada; solid mid-high local inference.","url":"https://hardware.branolabs.com/sku/rtx-4080-super"},{"id":"rtx-4070-ti-super","slug":"rtx-4070-ti-super","name":"NVIDIA GeForce RTX 4070 Ti Super 16GB","brand":"NVIDIA","category":"gpu","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Value 16GB Ada for smaller models.","url":"https://hardware.branolabs.com/sku/rtx-4070-ti-super"},{"id":"rx-7900-xtx","slug":"rx-7900-xtx","name":"AMD Radeon RX 7900 XTX 24GB","brand":"AMD","category":"gpu","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"24GB ROCm option; strong price/VRAM when drivers cooperate.","url":"https://hardware.branolabs.com/sku/rx-7900-xtx"},{"id":"rtx-a6000","slug":"rtx-a6000","name":"NVIDIA RTX A6000 48GB","brand":"NVIDIA","category":"gpu-workstation","vramGb":48,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Pro workstation ECC GDDR6; common on DE used KI listings.","url":"https://hardware.branolabs.com/sku/rtx-a6000"},{"id":"rtx-6000-ada","slug":"rtx-6000-ada","name":"NVIDIA RTX 6000 Ada 48GB","brand":"NVIDIA","category":"gpu-workstation","vramGb":48,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Ada pro 48GB; scarce and expensive used.","url":"https://hardware.branolabs.com/sku/rtx-6000-ada"},{"id":"rtx-a5000","slug":"rtx-a5000","name":"NVIDIA RTX A5000 24GB","brand":"NVIDIA","category":"gpu-workstation","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Pro 24GB alternative to consumer 3090/4090.","url":"https://hardware.branolabs.com/sku/rtx-a5000"},{"id":"ddr5-64gb-kit","slug":"ddr5-64gb-desktop-kit","name":"DDR5-6000 64GB kit (2×32) desktop","brand":"Generic","category":"ram","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":64,"watt":null,"software":null,"specSource":null,"aiNote":"Desktop high-cap kit; DRAM spike made these expensive in 2026.","url":"https://hardware.branolabs.com/sku/ddr5-64gb-desktop-kit"},{"id":"ddr5-128gb-kit","slug":"ddr5-5600-128gb-kit","name":"DDR5-5600 128GB kit (4×32) desktop","brand":"Generic","category":"ram","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":128,"watt":null,"software":null,"specSource":null,"aiNote":"CPU offload / large context local AI builds.","url":"https://hardware.branolabs.com/sku/ddr5-5600-128gb-kit"},{"id":"ddr5-ecc-64gb","slug":"ddr5-rdimm-64gb","name":"DDR5 ECC RDIMM 64GB (server module)","brand":"Generic","category":"ram-ecc","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":64,"watt":null,"software":null,"specSource":null,"aiNote":"Server ECC module; prices follow DRAMeXchange spot.","url":"https://hardware.branolabs.com/sku/ddr5-rdimm-64gb"},{"id":"ddr4-ecc-64gb","slug":"ddr4-rdimm-64gb","name":"DDR4 ECC RDIMM 64GB","brand":"Generic","category":"ram-ecc","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":64,"watt":null,"software":null,"specSource":null,"aiNote":"Cheaper ECC path for older Threadripper/EPYC boards.","url":"https://hardware.branolabs.com/sku/ddr4-rdimm-64gb"},{"id":"ddr5-ecc-512gb-set","slug":"ddr5-ecc-512gb-set","name":"DDR5 ECC 512GB set (8×64)","brand":"Generic","category":"ram-ecc","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":512,"watt":null,"software":null,"specSource":null,"aiNote":"Full-channel workstation RAM for large models in system RAM.","url":"https://hardware.branolabs.com/sku/ddr5-ecc-512gb-set"},{"id":"psu-1200w","slug":"psu-1200w-80plus-gold","name":"1200W 80+ Gold ATX PSU","brand":"Generic","category":"psu","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":1200,"software":null,"specSource":null,"aiNote":"Minimum comfort for dual high-end GPUs.","url":"https://hardware.branolabs.com/sku/psu-1200w-80plus-gold"},{"id":"psu-1600w","slug":"psu-1600w-80plus-platinum","name":"1600W 80+ Platinum ATX PSU","brand":"Generic","category":"psu","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":1600,"software":null,"specSource":null,"aiNote":"Multi-GPU / A6000 class builds.","url":"https://hardware.branolabs.com/sku/psu-1600w-80plus-platinum"},{"id":"mb-trx50","slug":"mb-trx50-threadripper","name":"TRX50 Threadripper motherboard","brand":"Generic","category":"motherboard","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Many PCIe lanes for multi-GPU local AI.","url":"https://hardware.branolabs.com/sku/mb-trx50-threadripper"},{"id":"mb-x670e","slug":"mb-x670e-am5","name":"X670E AM5 motherboard (4+ PCIe)","brand":"Generic","category":"motherboard","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Consumer multi-GPU capable boards.","url":"https://hardware.branolabs.com/sku/mb-x670e-am5"},{"id":"nvme-4tb","slug":"nvme-4tb-gen4","name":"4TB PCIe 4.0 NVMe SSD","brand":"Generic","category":"storage","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":null,"aiNote":"Model weight + dataset scratch space.","url":"https://hardware.branolabs.com/sku/nvme-4tb-gen4"},{"id":"ws-bundle-a6000","slug":"ki-workstation-a6000-class","name":"KI workstation bundle (A6000-class + 256GB+ ECC)","brand":"Lenovo/Generic","category":"workstation","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":null,"software":null,"specSource":null,"aiNote":"Representative DE used KI-workstation class; verify parts individually.","url":"https://hardware.branolabs.com/sku/ki-workstation-a6000-class"},{"id":"tesla-v100-16gb","slug":"tesla-v100-16gb","name":"NVIDIA Tesla V100 16GB (PCIe or SXM2)","brand":"NVIDIA","category":"gpu-server","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"Volta, 16GB HBM2, fast FP16 + 1st-gen Tensor Cores. PCIe ~250W, SXM2 ~300W. Passive: needs strong case airflow or a blower/fan shroud. SXM2 needs an SXM2-to-PCIe adapter board. Still works with current CUDA/PyTorch, but no BF16/FlashAttention-2.","url":"https://hardware.branolabs.com/sku/tesla-v100-16gb"},{"id":"tesla-v100-32gb","slug":"tesla-v100-32gb","name":"NVIDIA Tesla V100 32GB (PCIe or SXM2)","brand":"NVIDIA","category":"gpu-server","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"The 32GB server card (A100 has no 32GB version). Same Volta limits as 16GB: no BF16, no FlashAttention-2. SXM2 boards need an adapter; PCIe ~250W, passive cooling.","url":"https://hardware.branolabs.com/sku/tesla-v100-32gb"},{"id":"a100-40gb-pcie","slug":"a100-40gb-pcie","name":"NVIDIA A100 40GB PCIe","brand":"NVIDIA","category":"gpu-server","vramGb":40,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"Ampere datacenter, 40GB HBM2, BF16/TF32, MIG. ~250W, passive: needs server-grade airflow. Strong for training/inference; used prices still high.","url":"https://hardware.branolabs.com/sku/a100-40gb-pcie"},{"id":"a100-80gb-pcie","slug":"a100-80gb-pcie","name":"NVIDIA A100 80GB PCIe","brand":"NVIDIA","category":"gpu-server","vramGb":80,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":300,"software":null,"specSource":null,"aiNote":"Ampere, 80GB HBM2e, ~300W, passive. Fits 70B models at 8-bit on one card. Frequent target for fake eBay listings — check seller history.","url":"https://hardware.branolabs.com/sku/a100-80gb-pcie"},{"id":"tesla-p40-24gb","slug":"tesla-p40-24gb","name":"NVIDIA Tesla P40 24GB","brand":"NVIDIA","category":"gpu-server","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"Cheap 24GB, but Pascal has very slow FP16 (run FP32 or llama.cpp quantized). ~250W, passive, needs 8-pin EPS (CPU) power adapter. Fine for budget LLM inference, poor for training.","url":"https://hardware.branolabs.com/sku/tesla-p40-24gb"},{"id":"tesla-p100-16gb","slug":"tesla-p100-16gb","name":"NVIDIA Tesla P100 16GB PCIe","brand":"NVIDIA","category":"gpu-server","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"Pascal with HBM2 and fast FP16 (unlike P40), but no Tensor Cores. ~250W passive. Budget option; aging CUDA support.","url":"https://hardware.branolabs.com/sku/tesla-p100-16gb"},{"id":"tesla-t4-16gb","slug":"tesla-t4-16gb","name":"NVIDIA Tesla T4 16GB","brand":"NVIDIA","category":"gpu-server","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":70,"software":null,"specSource":null,"aiNote":"Turing, 16GB, only 70W, low-profile, no extra power connector. Passive: add a small fan. Good INT8/FP16 inference card for small servers.","url":"https://hardware.branolabs.com/sku/tesla-t4-16gb"},{"id":"nvidia-a10-24gb","slug":"nvidia-a10-24gb","name":"NVIDIA A10 24GB","brand":"NVIDIA","category":"gpu-server","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":150,"software":null,"specSource":null,"aiNote":"Ampere, 24GB GDDR6, ~150W, single slot, passive. BF16 support; good modern inference card when found used.","url":"https://hardware.branolabs.com/sku/nvidia-a10-24gb"},{"id":"nvidia-a40-48gb","slug":"nvidia-a40-48gb","name":"NVIDIA A40 48GB","brand":"NVIDIA","category":"gpu-server","vramGb":48,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":300,"software":null,"specSource":null,"aiNote":"Ampere, 48GB GDDR6, ~300W, passive dual-slot. Same chip class as RTX A6000 but needs server airflow.","url":"https://hardware.branolabs.com/sku/nvidia-a40-48gb"},{"id":"nvidia-l4-24gb","slug":"nvidia-l4-24gb","name":"NVIDIA L4 24GB","brand":"NVIDIA","category":"gpu-server","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":72,"software":null,"specSource":null,"aiNote":"Ada Lovelace, 24GB, only 72W, low-profile, FP8. Passive: needs airflow. Efficient inference card.","url":"https://hardware.branolabs.com/sku/nvidia-l4-24gb"},{"id":"tesla-m40-24gb","slug":"tesla-m40-24gb","name":"NVIDIA Tesla M40 24GB","brand":"NVIDIA","category":"gpu-server","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":250,"software":null,"specSource":null,"aiNote":"Very cheap 24GB, but Maxwell (2015): no fast FP16, compute 5.2, dropped by many newer frameworks/CUDA releases. ~250W passive. Only for tinkering with llama.cpp-style FP32/quantized inference.","url":"https://hardware.branolabs.com/sku/tesla-m40-24gb"},{"id":"instinct-mi50-32gb","slug":"instinct-mi50-32gb","name":"AMD Instinct MI50 32GB","brand":"AMD","category":"gpu-server","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":300,"software":null,"specSource":null,"aiNote":"Vega 20 (gfx906), 32GB HBM2, ~300W passive. ROCm 6.3.x was the last release with (deprecated) support; newer ROCm drops it. Cheap VRAM for llama.cpp/Vulkan users who accept driver pain.","url":"https://hardware.branolabs.com/sku/instinct-mi50-32gb"},{"id":"instinct-mi60-32gb","slug":"instinct-mi60-32gb","name":"AMD Instinct MI60 32GB","brand":"AMD","category":"gpu-server","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":300,"software":null,"specSource":null,"aiNote":"Same gfx906 family as MI50 with more CUs. Same ROCm end-of-support caveat. Passive, ~300W.","url":"https://hardware.branolabs.com/sku/instinct-mi60-32gb"},{"id":"instinct-mi100-32gb","slug":"instinct-mi100-32gb","name":"AMD Instinct MI100 32GB","brand":"AMD","category":"gpu-server","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":300,"software":null,"specSource":null,"aiNote":"CDNA (gfx908), 32GB HBM2, ~300W passive. Still listed as supported in ROCm 6.4. Needs server airflow.","url":"https://hardware.branolabs.com/sku/instinct-mi100-32gb"},{"id":"arc-a770-16gb","slug":"arc-a770-16gb","name":"Intel Arc A770 16GB","brand":"Intel","category":"gpu","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":225,"software":null,"specSource":null,"aiNote":"16GB for little money. AI via oneAPI/IPEX-LLM, OpenVINO, llama.cpp SYCL/Vulkan. Less plug-and-play than CUDA.","url":"https://hardware.branolabs.com/sku/arc-a770-16gb"},{"id":"arc-b580-12gb","slug":"arc-b580-12gb","name":"Intel Arc B580 12GB","brand":"Intel","category":"gpu","vramGb":12,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":190,"software":null,"specSource":null,"aiNote":"Battlemage, 12GB, ~190W. Good value for small models via oneAPI/OpenVINO/llama.cpp; 12GB limits model size.","url":"https://hardware.branolabs.com/sku/arc-b580-12gb"},{"id":"arc-pro-b60-24gb","slug":"arc-pro-b60-24gb","name":"Intel Arc Pro B60 24GB","brand":"Intel","category":"gpu-workstation","vramGb":24,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":200,"software":null,"specSource":null,"aiNote":"Battlemage workstation, 24GB GDDR6, 456 GB/s, TBP 200W (120–200W configurable), PCIe 5.0 x8. Sold via partners (e.g. Sparkle). oneAPI/OpenVINO; Linux multi-GPU.","url":"https://hardware.branolabs.com/sku/arc-pro-b60-24gb"},{"id":"rx-7900-xt","slug":"rx-7900-xt","name":"AMD Radeon RX 7900 XT 20GB","brand":"AMD","category":"gpu","vramGb":20,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":315,"software":null,"specSource":null,"aiNote":"RDNA3 (gfx1100), 20GB, ~315W. Officially ROCm-supported on Linux; good VRAM per euro.","url":"https://hardware.branolabs.com/sku/rx-7900-xt"},{"id":"rx-9070-xt","slug":"rx-9070-xt","name":"AMD Radeon RX 9070 XT 16GB","brand":"AMD","category":"gpu","vramGb":16,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":304,"software":null,"specSource":null,"aiNote":"RDNA4, 16GB, ~304W. ROCm support arrived later than for RDNA3 — check your ROCm version; Vulkan llama.cpp works.","url":"https://hardware.branolabs.com/sku/rx-9070-xt"},{"id":"radeon-pro-w7900","slug":"radeon-pro-w7900","name":"AMD Radeon Pro W7900 48GB","brand":"AMD","category":"gpu-workstation","vramGb":48,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":295,"software":null,"specSource":null,"aiNote":"RDNA3 (gfx1100), 48GB, ~295W, blower. ROCm-supported. Cheapest new 48GB card in many shops.","url":"https://hardware.branolabs.com/sku/radeon-pro-w7900"},{"id":"radeon-pro-w7800","slug":"radeon-pro-w7800","name":"AMD Radeon Pro W7800 32GB","brand":"AMD","category":"gpu-workstation","vramGb":32,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":null,"watt":260,"software":null,"specSource":null,"aiNote":"RDNA3 (gfx1100), 32GB, ~260W. ROCm-supported. (A 48GB W7800 variant also exists.)","url":"https://hardware.branolabs.com/sku/radeon-pro-w7800"},{"id":"mac-studio-m5-max-128gb","slug":"mac-studio-m5-max-128gb","name":"Apple Mac Studio M5 Max 128GB (2026)","brand":"Apple","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":614,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/128107","aiNote":"128GB unified memory at 614GB/s: runs 70B dense at Q4–Q6 and ~100B-class MoE comfortably. Needs the 18-core CPU / 40-core GPU chip. Prompt processing much slower than a big NVIDIA GPU; token generation is good.","url":"https://hardware.branolabs.com/sku/mac-studio-m5-max-128gb"},{"id":"mac-studio-m5-ultra-96gb","slug":"mac-studio-m5-ultra-96gb","name":"Apple Mac Studio M5 Ultra 96GB (2026, base Ultra)","brand":"Apple","category":"ai-desktop","vramGb":96,"unifiedMemoryGb":96,"bandwidthGBs":1200,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/128107","aiNote":"1.2TB/s bandwidth — fast token generation; 96GB fits 70B at Q4–Q8. Base config: 30-core CPU, 64-core GPU, 1TB.","url":"https://hardware.branolabs.com/sku/mac-studio-m5-ultra-96gb"},{"id":"mac-studio-m5-ultra-256gb","slug":"mac-studio-m5-ultra-256gb","name":"Apple Mac Studio M5 Ultra 256GB (2026)","brand":"Apple","category":"ai-desktop","vramGb":256,"unifiedMemoryGb":256,"bandwidthGBs":1200,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/128107","aiNote":"256GB/1.2TB/s: large MoE models (200B+ class at 4-bit) on one quiet box. Requires 36-core CPU / 80-core GPU chip.","url":"https://hardware.branolabs.com/sku/mac-studio-m5-ultra-256gb"},{"id":"mac-studio-m5-ultra-512gb","slug":"mac-studio-m5-ultra-512gb","name":"Apple Mac Studio M5 Ultra 512GB (2026)","brand":"Apple","category":"ai-desktop","vramGb":512,"unifiedMemoryGb":512,"bandwidthGBs":1200,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/128107","aiNote":"512GB: the largest single-box local LLM memory below datacenter gear; fits very large MoE models at 4-bit. Expensive; prompt processing on long contexts is the weak point.","url":"https://hardware.branolabs.com/sku/mac-studio-m5-ultra-512gb"},{"id":"mac-studio-m3-ultra-256gb","slug":"mac-studio-m3-ultra-256gb","name":"Apple Mac Studio M3 Ultra 256GB (2025)","brand":"Apple","category":"ai-desktop","vramGb":256,"unifiedMemoryGb":256,"bandwidthGBs":819,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/122211","aiNote":"Previous generation (819GB/s). Good used/refurb value for big models; no GPU Neural Accelerators, so prompt processing slower than M5.","url":"https://hardware.branolabs.com/sku/mac-studio-m3-ultra-256gb"},{"id":"mac-studio-m4-max-128gb","slug":"mac-studio-m4-max-128gb","name":"Apple Mac Studio M4 Max 128GB (2025)","brand":"Apple","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":546,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-us/122211","aiNote":"Previous generation, 546GB/s (16-core CPU/40-core GPU). Solid used/refurb pick for 70B-class models.","url":"https://hardware.branolabs.com/sku/mac-studio-m4-max-128gb"},{"id":"mac-mini-m5-pro-64gb","slug":"mac-mini-m5-pro-64gb","name":"Apple Mac mini M5 Pro 64GB (2026)","brand":"Apple","category":"ai-desktop","vramGb":64,"unifiedMemoryGb":64,"bandwidthGBs":307,"capacityGb":null,"watt":null,"software":"macOS. Best stack: MLX, llama.cpp (Metal), Ollama/LM Studio. No CUDA: most PyTorch training recipes and CUDA-only tools won't run or run slowly (MPS backend).","specSource":"https://support.apple.com/en-gb/128108","aiNote":"64GB max (18-core CPU/20-core GPU M5 Pro), 307GB/s. Fine for 30B-class models and small 70B quants; cheap always-on agent box, not a big-model machine.","url":"https://hardware.branolabs.com/sku/mac-mini-m5-pro-64gb"},{"id":"nvidia-dgx-spark","slug":"nvidia-dgx-spark","name":"NVIDIA DGX Spark (GB10, 128GB)","brand":"NVIDIA","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":240,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"128GB coherent LPDDR5X but only 273GB/s: great for CUDA dev, fine-tuning and running 70B–200B (FP4) models, but token generation is slower than Mac Ultra or a big GPU. 240W external PSU (GB10 TDP 140W). Two can be linked via ConnectX-7.","url":"https://hardware.branolabs.com/sku/nvidia-dgx-spark"},{"id":"asus-ascent-gx10","slug":"asus-ascent-gx10","name":"ASUS Ascent GX10 (GB10, 128GB)","brand":"ASUS","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/asus-ascent-gx10"},{"id":"dell-pro-max-gb10","slug":"dell-pro-max-gb10","name":"Dell Pro Max with GB10 (FCM1253, 128GB)","brand":"Dell","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/dell-pro-max-gb10"},{"id":"lenovo-thinkstation-pgx","slug":"lenovo-thinkstation-pgx","name":"Lenovo ThinkStation PGX (GB10, 128GB)","brand":"Lenovo","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/lenovo-thinkstation-pgx"},{"id":"msi-edgexpert","slug":"msi-edgexpert","name":"MSI EdgeXpert MS-C931 (GB10, 128GB)","brand":"MSI","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/msi-edgexpert"},{"id":"hp-zgx-nano-g1n","slug":"hp-zgx-nano-g1n","name":"HP ZGX Nano G1n AI Station (GB10, 128GB)","brand":"HP","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/hp-zgx-nano-g1n"},{"id":"gigabyte-ai-top-atom","slug":"gigabyte-ai-top-atom","name":"Gigabyte AI TOP ATOM (GB10, 128GB)","brand":"Gigabyte","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":273,"capacityGb":null,"watt":null,"software":"NVIDIA DGX OS (Ubuntu-based, Arm64). Full CUDA, TensorRT-LLM, vLLM, NIM. Some x86-only Python wheels/containers need Arm builds.","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-spark/","aiNote":"Partner GB10 system: same chip, memory and 273GB/s as DGX Spark; differs in storage, cooling, warranty and price. 64GB OEM variants also exist — check the config.","url":"https://hardware.branolabs.com/sku/gigabyte-ai-top-atom"},{"id":"framework-desktop-395-128gb","slug":"framework-desktop-395-128gb","name":"Framework Desktop (Ryzen AI Max+ 395, 128GB)","brand":"Framework","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":256,"capacityGb":null,"watt":null,"software":"Windows 11 or Linux. GPU compute via ROCm (Strix Halo support still maturing), Vulkan llama.cpp works well; no CUDA. Up to 96GB assignable to the GPU in BIOS.","specSource":"https://www.amd.com/en/products/processors/laptop/ryzen/ai-300-series/amd-ryzen-ai-max-plus-395.html","aiNote":"128GB LPDDR5X-8000 on a 256-bit bus (256GB/s theoretical, ~210–215 real): loads 70B-class models; dense 70B ≈ 4–6 tok/s, MoE models much faster. Cheapest way to 96GB of GPU-usable memory. Repairable 4.5L mini-ITX, Linux-friendly.","url":"https://hardware.branolabs.com/sku/framework-desktop-395-128gb"},{"id":"gmktec-evo-x2-128gb","slug":"gmktec-evo-x2-128gb","name":"GMKtec EVO-X2 (Ryzen AI Max+ 395, 128GB)","brand":"GMKtec","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":256,"capacityGb":null,"watt":null,"software":"Windows 11 or Linux. GPU compute via ROCm (Strix Halo support still maturing), Vulkan llama.cpp works well; no CUDA. Up to 96GB assignable to the GPU in BIOS.","specSource":"https://www.amd.com/en/products/processors/laptop/ryzen/ai-300-series/amd-ryzen-ai-max-plus-395.html","aiNote":"128GB LPDDR5X-8000 on a 256-bit bus (256GB/s theoretical, ~210–215 real): loads 70B-class models; dense 70B ≈ 4–6 tok/s, MoE models much faster. Cheapest way to 96GB of GPU-usable memory. Ships from China for many buyers — check import VAT and warranty.","url":"https://hardware.branolabs.com/sku/gmktec-evo-x2-128gb"},{"id":"hp-z2-mini-g1a-128gb","slug":"hp-z2-mini-g1a-128gb","name":"HP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128GB)","brand":"HP","category":"ai-desktop","vramGb":128,"unifiedMemoryGb":128,"bandwidthGBs":256,"capacityGb":null,"watt":300,"software":"Windows 11 or Linux. GPU compute via ROCm (Strix Halo support still maturing), Vulkan llama.cpp works well; no CUDA. Up to 96GB assignable to the GPU in BIOS.","specSource":"https://www.amd.com/en/products/processors/laptop/ryzen/ai-300-series/amd-ryzen-ai-max-plus-395.html","aiNote":"128GB LPDDR5X-8000 on a 256-bit bus (256GB/s theoretical, ~210–215 real): loads 70B-class models; dense 70B ≈ 4–6 tok/s, MoE models much faster. Cheapest way to 96GB of GPU-usable memory. Business workstation, internal 300W PSU, ISV certification.","url":"https://hardware.branolabs.com/sku/hp-z2-mini-g1a-128gb"},{"id":"nvidia-dgx-station-gb300","slug":"nvidia-dgx-station-gb300","name":"NVIDIA DGX Station (GB300)","brand":"NVIDIA","category":"ai-desktop","vramGb":748,"unifiedMemoryGb":748,"bandwidthGBs":7100,"capacityGb":null,"watt":1600,"software":"DGX OS / Ubuntu, full CUDA stack. Sold via OEM partners (e.g. ASUS ExpertCenter Pro ET900N G3).","specSource":"https://www.nvidia.com/en-us/products/workstations/dgx-station/","aiNote":"Deskside datacenter-class: 252GB HBM3e at ~7.1TB/s on the GPU plus 496GB LPDDR5X (748GB coherent). Six-figure price, ~1.6kW. Listed for completeness, not a hobby buy.","url":"https://hardware.branolabs.com/sku/nvidia-dgx-station-gb300"},{"id":"samsung-9100-pro-2tb","slug":"samsung-9100-pro-2tb","name":"Samsung 9100 PRO 2TB","brand":"Samsung","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://semiconductor.samsung.com/consumer-storage/internal-ssd/9100-pro/","aiNote":"PCIe 5.0 NVMe, up to 14,700 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/samsung-9100-pro-2tb"},{"id":"samsung-9100-pro-4tb","slug":"samsung-9100-pro-4tb","name":"Samsung 9100 PRO 4TB","brand":"Samsung","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://semiconductor.samsung.com/consumer-storage/internal-ssd/9100-pro/","aiNote":"PCIe 5.0 NVMe, up to 14,800 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/samsung-9100-pro-4tb"},{"id":"samsung-9100-pro-8tb","slug":"samsung-9100-pro-8tb","name":"Samsung 9100 PRO 8TB","brand":"Samsung","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":8000,"watt":null,"software":null,"specSource":"https://semiconductor.samsung.com/consumer-storage/internal-ssd/9100-pro/","aiNote":"PCIe 5.0 NVMe, up to 14,800 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 8TB holds ~177 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/samsung-9100-pro-8tb"},{"id":"samsung-990-pro-2tb","slug":"samsung-990-pro-2tb","name":"Samsung 990 PRO 2TB","brand":"Samsung","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://semiconductor.samsung.com/consumer-storage/internal-ssd/990-pro/","aiNote":"PCIe 4.0 NVMe, up to 7,450 MB/s read: a 40GB model file (70B at Q4) loads in roughly 7s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: a simple M.2 heatsink (most boards include one) keeps sustained reads at full speed.","url":"https://hardware.branolabs.com/sku/samsung-990-pro-2tb"},{"id":"samsung-990-pro-4tb","slug":"samsung-990-pro-4tb","name":"Samsung 990 PRO 4TB","brand":"Samsung","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://semiconductor.samsung.com/consumer-storage/internal-ssd/990-pro/","aiNote":"PCIe 4.0 NVMe, up to 7,450 MB/s read: a 40GB model file (70B at Q4) loads in roughly 7s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: a simple M.2 heatsink (most boards include one) keeps sustained reads at full speed.","url":"https://hardware.branolabs.com/sku/samsung-990-pro-4tb"},{"id":"wd-sn8100-2tb","slug":"wd-sn8100-2tb","name":"WD_BLACK SN8100 2TB","brand":"WD / SanDisk","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://documents.sandisk.com/content/dam/asset-library/en_us/assets/public/sandisk/product/internal-drives/wd-black-ssd/data-sheet-wd-black-sn8100-nvme-ssd.pdf","aiNote":"PCIe 5.0 NVMe, up to 14,900 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/wd-sn8100-2tb"},{"id":"wd-sn8100-4tb","slug":"wd-sn8100-4tb","name":"WD_BLACK SN8100 4TB","brand":"WD / SanDisk","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://documents.sandisk.com/content/dam/asset-library/en_us/assets/public/sandisk/product/internal-drives/wd-black-ssd/data-sheet-wd-black-sn8100-nvme-ssd.pdf","aiNote":"PCIe 5.0 NVMe, up to 14,900 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/wd-sn8100-4tb"},{"id":"wd-sn850x-4tb","slug":"wd-sn850x-4tb","name":"WD_BLACK SN850X 4TB","brand":"WD / SanDisk","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://www.westerndigital.com/products/internal-drives/wd-black-sn850x-nvme-ssd","aiNote":"PCIe 4.0 NVMe, up to 7,300 MB/s read: a 40GB model file (70B at Q4) loads in roughly 7s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: a simple M.2 heatsink (most boards include one) keeps sustained reads at full speed.","url":"https://hardware.branolabs.com/sku/wd-sn850x-4tb"},{"id":"wd-sn850x-8tb","slug":"wd-sn850x-8tb","name":"WD_BLACK SN850X 8TB","brand":"WD / SanDisk","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":8000,"watt":null,"software":null,"specSource":"https://www.westerndigital.com/products/internal-drives/wd-black-sn850x-nvme-ssd","aiNote":"PCIe 4.0 NVMe, up to 7,200 MB/s read: a 40GB model file (70B at Q4) loads in roughly 7s from a cold cache. 8TB holds ~177 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: a simple M.2 heatsink (most boards include one) keeps sustained reads at full speed.","url":"https://hardware.branolabs.com/sku/wd-sn850x-8tb"},{"id":"crucial-t705-2tb","slug":"crucial-t705-2tb","name":"Crucial T705 2TB","brand":"Crucial","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://www.crucial.com/ssd/t705/ct2000t705ssd3","aiNote":"PCIe 5.0 NVMe, up to 14,500 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/crucial-t705-2tb"},{"id":"crucial-t705-4tb","slug":"crucial-t705-4tb","name":"Crucial T705 4TB","brand":"Crucial","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://www.crucial.com/ssd/t705/ct4000t705ssd3","aiNote":"PCIe 5.0 NVMe, up to 14,100 MB/s read: a 40GB model file (70B at Q4) loads in roughly 4s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/crucial-t705-4tb"},{"id":"crucial-t710-2tb","slug":"crucial-t710-2tb","name":"Crucial T710 2TB","brand":"Crucial","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://www.crucial.com/ssd/t710/ct2000t710ssd8","aiNote":"PCIe 5.0 NVMe, up to 14,500 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/crucial-t710-2tb"},{"id":"crucial-t710-4tb","slug":"crucial-t710-4tb","name":"Crucial T710 4TB","brand":"Crucial","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://www.crucial.com/ssd/t710/ct4000t710ssd8","aiNote":"PCIe 5.0 NVMe, up to 14,500 MB/s read: a 40GB model file (70B at Q4) loads in roughly 3s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/crucial-t710-4tb"},{"id":"corsair-mp700-pro-2tb","slug":"corsair-mp700-pro-2tb","name":"Corsair MP700 PRO 2TB","brand":"Corsair","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://www.corsair.com/us/en/c/storage/m2-ssds","aiNote":"PCIe 5.0 NVMe, up to 12,400 MB/s read: a 40GB model file (70B at Q4) loads in roughly 4s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/corsair-mp700-pro-2tb"},{"id":"kingston-fury-renegade-4tb","slug":"kingston-fury-renegade-4tb","name":"Kingston FURY Renegade 4TB (PCIe 4.0)","brand":"Kingston","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":4000,"watt":null,"software":null,"specSource":"https://www.kingston.com/en/ssd/gaming/kingston-fury-renegade-nvme-m2-ssd","aiNote":"PCIe 4.0 NVMe, up to 7,300 MB/s read: a 40GB model file (70B at Q4) loads in roughly 7s from a cold cache. 4TB holds ~88 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: a simple M.2 heatsink (most boards include one) keeps sustained reads at full speed.","url":"https://hardware.branolabs.com/sku/kingston-fury-renegade-4tb"},{"id":"seagate-firecuda-540-2tb","slug":"seagate-firecuda-540-2tb","name":"Seagate FireCuda 540 2TB","brand":"Seagate","category":"ssd","vramGb":null,"unifiedMemoryGb":null,"bandwidthGBs":null,"capacityGb":2000,"watt":null,"software":null,"specSource":"https://www.seagate.com/products/gaming-drives/pc-gaming/firecuda-540-ssd/","aiNote":"PCIe 5.0 NVMe, up to 10,000 MB/s read: a 40GB model file (70B at Q4) loads in roughly 5s from a cold cache. 2TB holds ~44 such models. Not a VRAM substitute: llama.cpp mmap or DeepSpeed/accelerate NVMe offload streaming weights from SSD is 10-100x slower than VRAM or RAM, so only for experiments. Cooling: Gen5 drives throttle without airflow; use the motherboard M.2 heatsink or the heatsink version. Full speed needs a CPU-attached PCIe 5.0 M.2 slot.","url":"https://hardware.branolabs.com/sku/seagate-firecuda-540-2tb"}],"offers":[{"skuId":"rtx-4090","source":"idealo.de","url":"https://www.idealo.de/preisvergleich/OffersOfProduct/202126281_-geforce-rtx-4090-palit.html","title":"Palit GeForce RTX 4090 (Idealo low)","price":2899.99,"currency":"EUR","priceEurApprox":2899.99,"priceExclVat":null,"condition":"new","region":"DE","origin":null,"freshness":"stale","lastChecked":"2026-10-22T08:41:13.166Z","trust":"high"},{"skuId":"rtx-4090","source":"idealo.de","url":"https://www.idealo.de/preisvergleich/OffersOfProduct/202125132_-geforce-rtx-4090-msi.html","title":"MSI GeForce RTX 4090 (Idealo 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