45HomeLab HL15 2.0 (Fully Built & Burned In)

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45HomeLab HL15 2.0 (Fully Built & Burned In)

Processor
AMD EPYC 7002 / 7003 series
Memory (RAM)
16, 32, 64, 128, 256 or 512 GB
Launch price
$2,920

Product page (opens in a new tab) Full AI report

Configurations

Pick one to see which models it runs. More memory lets larger models fit; bandwidth sets how fast they answer.

Configuration Memory Usable for AI Bandwidth LLMs that run well Launch price
AMD EPYC 7002 / 7003 series 16.0 GB 12.0 GB 205 GB/s 352 of 619 $2,920
AMD EPYC 7002 / 7003 series 32.0 GB 26.2 GB 205 GB/s 395 of 619 —
AMD EPYC 7002 / 7003 series 64.0 GB 54.4 GB 205 GB/s 420 of 619 —
AMD EPYC 7002 / 7003 series 128 GB 113 GB 205 GB/s 441 of 619 —
AMD EPYC 7002 / 7003 series 256 GB 230 GB 205 GB/s 457 of 619 —
AMD EPYC 7002 / 7003 series 512 GB 471 GB 205 GB/s 459 of 619 —

Specifications 32.0 GB configuration

Maker45HomeLab
TypeNAS
ProcessorAMD EPYC 7002 / 7003 series NAS (32 GB)
Memory (RAM)32.0 GB
Usable for AI models26.2 GB
Memory bandwidth205 GB/s
FP16 compute1.0 TFLOPS
Runs models onCPU cores
Drive bays15x 3.5" SATA/SAS (direct-wired backplane), 4U
NAS systemRocky Linux 9 with Houston UI
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 ECC RDIMM/LRDIMM · 8 slots · up to 512 GB per the maker · ECC
Graphics card optionsPCIe: ASRock Rack ROMED8-2T motherboard (multiple full-length PCIe slots; exact count not stated on the store page….
NotesAMD EPYC 7252 (options: EPYC 7272, 7282, 7452). Server-class AMD EPYC with 8-channel DDR4 and up to 512 GB ECC RAM, plus full-size PCIe slots and a 1000 W ATX PSU, so one or more NVIDIA GPUs can be added. No AI app is preinstalled: you run Ollama in Docker/Podman on Rocky Linux, or install TrueNAS/Proxmox/Unraid.
Product pagestore.45homelab.com (opens in a new tab)

Running AI on the 45HomeLab HL15 2.0 (Fully Built & Burned In)

Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 26.2 GB for them after the NAS system and its storage services. The grades below assume the NAS isn’t busy with backups or media work at the same time. More memory is the upgrade that matters most: see the configurations.

Apps you can install to run models

AppHow it installs
Ollama In a container (Docker)
Open WebUI In a container (Docker)
LocalAI In a container (Docker)

Apps that run LLMs on a NAS, with their container images

Best LLMs for the 45HomeLab HL15 2.0 (Fully Built & Burned In) 32.0 GB

Quality Model Quant Memory Speed Runs
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q4_K_M 24.8 GB 40.2 tok/s Runs welltight fit
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 35B-A3BOpenBMB Q4_K_M 24.3 GB 40.2 tok/s Runs welltight fit
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 35B-A3BAlibaba Q4_K_M 24.8 GB 40.2 tok/s Runs welltight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Nex N2 Mini (35B-A3B)Nex-AGI Q4_K_M 24.3 GB 40.2 tok/s Runs welltight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q4_K_M 18.8 GB 32.7 tok/s Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. KAT-Coder V2.5 Dev (35B-A3B)Kuaishou Q4_K_M 24.0 GB 40.2 tok/s Runs welltight fit
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Sage-A1.5 35B-A3BInternScience Q4_K_M 24.8 GB 40.2 tok/s Runs welltight fit
83Great quality (A) · 83 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. GLM-4.7 Flash (30B-A3B)Zhipu AI Q4_K_M 22.2 GB 40.2 tok/s Runs great
85Excellent quality (A+) · 85 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 35B-A3BDeepReinforce Q4_K_M 24.8 GB 40.2 tok/s Runs welltight fit
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Apodex 1.1 Mini (35B-A3B)Apodex Q4_K_M 24.8 GB 40.2 tok/s Runs welltight fit

Best Image models for the 45HomeLab HL15 2.0 (Fully Built & Burned In) 32.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP8 20.2 GB 2.7 min Very slow
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs FP8 19.9 GB 67 s Slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q8 GGUF 18.9 GB 17.3 min Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at NF4, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Ideogram 4Ideogram NF4 21.8 GB 18.8 min Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 12.8 GB 4.5 min Very slow
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu FP8 14.5 GB 2.0 min Slow

Best Video models for the 45HomeLab HL15 2.0 (Fully Built & Burned In) 32.0 GB

Quality Model Quant Memory Speed Runs
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 20.3 GB 7.8 h Very slowencoder unloaded after use
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP8 24.6 GB 5.4 h Very slowtight fit
70Great quality (A) · 70 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.2 S2V 14B (speech to video)Alibaba Q4 GGUF 21.6 GB 13.7 h Very slow
68Good quality (B) · 68 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 I2V 14B 480PAlibaba Q4 GGUF 20.6 GB 12.3 h Very slow
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.3Lightricks Q4 GGUF 24.5 GB 5.8 h Very slowtight fit · encoder unloaded after use

Best Decision models for the 45HomeLab HL15 2.0 (Fully Built & Burned In) 32.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI F16 3.8 GB 44 ms Runs great
68Good quality (B) · 68 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 22MMeta Q8_0 0.7 GB 103 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 345 ms Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 3.6 GB 780 ms Slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 3.6 GB 780 ms Slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q8_0 7.3 GB 5.2 s Very slow
66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. GLiClass Base v3Knowledgator Q8_0 0.8 GB 136 ms Runs well
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI Q8_0 1.7 GB 574 ms Slow

Other products with the AMD EPYC 7002 / 7003 series NAS (32 GB)

Spec sources

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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