FRAMEWORK DESKTOP DIY, RYZEN AI MAX 385, 32GB
product: Framework Desktop DIY, Ryzen AI Max 385, 32GB category: Mini PCs · also under Workstations brand: Framework memory: 32GB unified · 256 GB/s [2] notes: DIY Edition, storage not included. Soldered LPDDR5x-8000. price: now: $1,269 (Framework, official list, 2026-11-13) [1] BUY NOW AT FRAMEWORK → since_first: UP 15% SINCE FEB 25, 2025 first_record: 2025-02-25 (price in the paid export) change: 1d: — 7d: — 14d: =0.0% 30d: =0.0% 90d: — 180d: =0.0% price_hikes: 3 since Feb 2025 availability: preorder
UP 15% SINCE FEB 25, 2025 — now $1,269. BUY NOW AT FRAMEWORK →
3 PRICE HIKES SINCE FEB 2025
LATEST STEP UP: +$60 (+5.0%), FIRST SEEN MAR 19, 2026
PRICE TREND (shape since first record)
now $1,269 │ ███████████████████████ │ ███████████████████████ │ ▄▄███████████████████████ │ █████████████████████████ │ █████████████████████████ │ ▄▄▄ █████████████████████████ │ ███░█████████████████████████ │██████████████████████████████░███░█████████████████████████ └──────────────────────────────────────────────────────────── 2025-02-25 2026-11-13 █ recorded price ░ gap between records · shape only; past prices are in the paid export
PRICE HISTORY (last 7 days)
| 2026-11-13 | $1,269 | Framework | preorder | [1] |
31 older records back to Feb 25, 2025 (every price, date and source) are in the paid export (YAML / CSV).
PAIRS WELL WITH (add-ons, not price-tracked · all peripherals)
Samsung 990 PRO 4TB NVMe SSD (MZ-V9P4T0B/AM): why: Model files are big: a 70B Q8 file alone is ~75 GB. Framework Desktop DIY ships without storage. buy: BUY ON AMAZON → Noctua NF-A12x25 PWM 120mm fan: why: Quiet 120mm fan; Framework Desktop takes a standard 120mm fan. buy: BUY ON AMAZON → CalDigit TS4 Thunderbolt 4 / USB4 dock: why: Adds ports to USB4 Strix Halo boxes and Macs; 18 ports, 98W charging. buy: BUY ON AMAZON → APC Back-UPS Pro 1500VA (BR1500MS2): why: Keeps a long run or a model download alive through a short outage. buy: BUY ON AMAZON →
CAN RUN — LOCAL MODELS THAT FIT
memory: 32GB unified · usable for models ≈ 24 GB (rule) bandwidth: 256 GB/s [2] largest_fit: OLMo 3.1 32B Q4_K_M fits: 10 of 33 model files (excluding the Llama 2 7B reference) note: fit = weights + KV cache at 8,192 tokens + 10% runtime overhead
| Nemotron 3.5 Super 120B-A12B (MoE) | Q8_0 | 128.5 GB | 141.4 GB [3] | no | no published run |
| Nemotron 3.5 Super 120B-A12B (MoE) | Q4_0 | 72.1 GB | 79.4 GB [3] | no | no published run |
| gpt-oss 120B (MoE) | MXFP4 | 63.4 GB | 70.0 GB [4] | no | no published run |
| Llama 4 Scout 109B-A17B (MoE) | Q8_0 | 114.5 GB | 127.6 GB [5] | no | no published run |
| Llama 4 Scout 109B-A17B (MoE) | Q4_K_M | 65.4 GB | 73.5 GB [5] | no | no published run |
| Nemotron 3.5 Bolt 74B-A9B (MoE) | BF16 | 148.2 GB | 163.1 GB [6] | no | no published run |
| Nemotron 3.5 Bolt 74B-A9B (MoE) | Q8_0 | 78.9 GB | 86.8 GB [6] | no | no published run |
| Nemotron 3.5 Bolt 74B-A9B (MoE) | Q4_K_XL | 50.2 GB | 55.3 GB [6] | no | no published run |
| Llama 3.3 70B | f16 | 141.1 GB | 157.9 GB [7] | no | no published run |
| Llama 3.3 70B | Q8_0 | 75.0 GB | 85.2 GB [7] | no | no published run |
| Llama 3.3 70B | Q4_K_M | 42.5 GB | 49.5 GB [7] | no | no published run |
| OLMo 3.1 32B | bf16 | 64.5 GB | 72.3 GB [8] | no | no published run |
| OLMo 3.1 32B | Q8_0 | 34.3 GB | 39.0 GB [8] | no | no published run |
| OLMo 3.1 32B | Q4_K_M | 19.5 GB | 22.8 GB [8] | YES | no published run |
| Nemotron 3.5 Lightning 30B-A3B (MoE) | BF16 | 63.2 GB | 69.5 GB [9] | no | no published run |
| Nemotron 3.5 Lightning 30B-A3B (MoE) | Q8_0 | 33.6 GB | 37.0 GB [9] | no | no published run |
| Nemotron 3.5 Lightning 30B-A3B (MoE) | Q4_0 | 18.9 GB | 20.8 GB [9] | YES | no published run |
| Gemma 4 31B | BF16 | 61.4 GB | 69.1 GB [10] | no | no published run |
| Gemma 4 31B | Q8_0 | 32.6 GB | 37.4 GB [10] | no | no published run |
| Gemma 4 31B | Q4_K_M | 18.3 GB | 21.7 GB [10] | YES | no published run |
| Granite 4.2 30B | bf16 | 58.6 GB | 66.6 GB [11] | no | no published run |
| Granite 4.2 30B | Q8_0 | 31.1 GB | 36.4 GB [11] | no | no published run |
| Granite 4.2 30B | Q4_K_M | 17.7 GB | 21.6 GB [11] | YES | no published run |
| Gemma 4 26B-A4B (MoE) | BF16 | 50.5 GB | 55.9 GB [12] | no | no published run |
| Gemma 4 26B-A4B (MoE) | Q8_0 | 26.9 GB | 29.9 GB [12] | TIGHT | no published run |
| Gemma 4 26B-A4B (MoE) | Q4_K_M | 16.9 GB | 19.0 GB [12] | YES | no published run |
| gpt-oss 20B | MXFP4 | 12.1 GB | 13.5 GB [13] | YES | no published run |
| Phi-4 14B | F16 | 29.3 GB | 33.9 GB [14] | no | no published run |
| Phi-4 14B | Q8_0 | 15.6 GB | 18.8 GB [14] | YES | no published run |
| Phi-4 14B | Q4_K_M | 8.9 GB | 11.5 GB [14] | YES | no published run |
| Gemma 4 12B | BF16 | 23.8 GB | 26.7 GB [15] | TIGHT | no published run |
| Gemma 4 12B | Q8_0 | 12.7 GB | 14.4 GB [15] | YES | no published run |
| Gemma 4 12B | Q4_K_M | 7.1 GB | 8.3 GB [15] | YES | no published run |
| Llama 2 7B (llama.cpp reference benchmark model) | Q8_0 | 7.2 GB | 12.2 GB [16] | YES | no published run |
| Llama 2 7B (llama.cpp reference benchmark model) | Q4_0 | 3.8 GB | 8.5 GB [16] | YES | no published run |
WHERE TO BUY
official: BUY NOW → Framework retailers: not tracked yet (partner programs pending)
SOURCES
Current sources only. Every older price point and its source is in the paid export.
| # | what | source | fetched |
|---|---|---|---|
| [1] | Framework Desk 32GB $1,269 on 2026-11-13 — Comparison page: 'Max 385 - 32GB' starting at $1,269.00, pre-ord... | frame.work/products/desktop-diy-amd-aimax300/comparison | 2026-11-13 |
| [2] | Framework: 256GB/s for Ryzen AI Max | frame.work/blog/introducing-the-framework-desktop | 2026-11-13 |
| [3] | Nemotron 3.5 Super 120B-A12B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/ggml-org/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-GGUF | 2026-11-13 |
| [4] | gpt-oss 120B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/ggml-org/gpt-oss-120b-GGUF | 2026-11-13 |
| [5] | Llama 4 Scout 109B-A17B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF | 2026-11-13 |
| [6] | Nemotron 3.5 Bolt 74B-A9B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-GGUF | 2026-11-13 |
| [7] | Llama 3.3 70B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/bartowski/Llama-3.3-70B-Instruct-GGUF | 2026-11-13 |
| [8] | OLMo 3.1 32B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/bartowski/allenai_Olmo-3.1-32B-Instruct-GGUF | 2026-11-13 |
| [9] | Nemotron 3.5 Lightning 30B-A3B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/ggml-org/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF | 2026-11-13 |
| [10] | Gemma 4 31B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/gemma-4-31B-it-GGUF | 2026-11-13 |
| [11] | Granite 4.2 30B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/ibm-granite/granite-4.2-30b-GGUF | 2026-11-13 |
| [12] | Gemma 4 26B-A4B (MoE): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF | 2026-11-13 |
| [13] | gpt-oss 20B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/ggml-org/gpt-oss-20b-GGUF | 2026-11-13 |
| [14] | Phi-4 14B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/phi-4-GGUF | 2026-11-13 |
| [15] | Gemma 4 12B: GGUF sizes + config.json (KV cache at 8k) | huggingface.co/unsloth/gemma-4-12b-it-GGUF | 2026-11-13 |
| [16] | Llama 2 7B (llama.cpp reference benchmark model): GGUF sizes + config.json (KV cache at 8k) | huggingface.co/TheBloke/Llama-2-7B-GGUF | 2026-11-13 |