ACEMAGIC N3A

Products · · NAS

ACEMAGIC N3A

Processor
AMD Ryzen Embedded R2514 / R2544
Memory (RAM)
8, 16, 32 or 64 GB
Launch price
$309
Released
2026

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 Ryzen Embedded R2514 / R2544 · ships without memory; with 8 GB fitted 8.0 GB 5.2 GB 21 GB/s 96 of 622 $309
AMD Ryzen Embedded R2514 / R2544 · ships without memory; with 16 GB fitted 16.0 GB 12.0 GB 21 GB/s 105 of 622 —
AMD Ryzen Embedded R2514 / R2544 · ships without memory; with 32 GB fitted 32.0 GB 26.2 GB 21 GB/s 107 of 622 —
AMD Ryzen Embedded R2514 / R2544 · upgraded to the maker's maximum 64.0 GB 54.4 GB 21 GB/s 107 of 622 —

Specifications 8.0 GB configuration

MakerACEMAGIC
TypeNAS
ProcessorAMD Ryzen Embedded R2514 / R2544 NAS (8 GB) · ships without memory; with 8 GB fitted
Memory (RAM)8.0 GB
Usable for AI models5.2 GB
Memory bandwidth21 GB/s
FP16 compute0.1 TFLOPS
Runs models onCPU cores
Drive bays4x SATA 3.5/2.5-inch (30 TB each) + 2x M.2 2280 NVMe PCIe 3.0 x4 (8 TB each; 136 TB total claimed)
NAS systemBarebone, no OS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4-3200 SO-DIMM · 2 slots · up to 64.0 GB per the maker
NotesAMD Ryzen Embedded R2544 (Zen+, 12 nm, 3.35-3.7 GHz). Two DDR4 slots give room for 7-14B quantized models, but the 4-core Zen+ CPU and old Radeon iGPU mean slow CPU-only inference.
Product pageacemagic.com (opens in a new tab)

Running AI on the ACEMAGIC N3A

It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 5.2 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)

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

Best LLMs for the ACEMAGIC N3A 8.0 GB

Quality Model Quant Memory Speed Runs
65Good quality (B) · 65 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4BNVIDIA Q5_K_M 4.3 GB 3.8 tok/s Slow
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q5_K_M 4.2 GB 3.6 tok/s Slow
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.2 3BBOSS Zhipin (Nanbeige) Q4_K_M 5.0 GB 4.4 tok/s Slowtight fit
50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q3_K_M 5.1 GB 17.1 tok/s Runs welltight fit
41Fair quality (C) · 41 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR 2 (3B-A0.6B)Baidu Q4_K_M 3.6 GB 27.5 tok/s Runs well
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 4BAlibaba Q4_K_M 4.1 GB 3.9 tok/s Slow
59Good quality (B) · 59 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. TMax 4BAi2 Q5_K_M 4.3 GB 3.6 tok/s Slow
52Fair quality (C) · 52 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2BGoogle Q3_K_M 3.6 GB 10.2 tok/s Runs well
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q3_K_M 5.1 GB 5.2 tok/s Slowtight fit
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Agents-A1 4BInternScience Q4_K_M 4.1 GB 4.0 tok/s Slow

Best Image models for the ACEMAGIC N3A 8.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 4.3 GB 28.6 min Very slowCPU offload
72Great quality (A) · 72 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs Q4 GGUF 4.6 GB 4.2 min Very slowtight fit · encoder unloaded after use
39Basic quality (D) · 39 of 100: how capable the model is at FP8, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. SDXL TurboStability AI FP8 4.2 GB 27 s Runs well
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) FP8 4.4 GB 9.8 min Very slowCPU offload
81Great quality (A) · 81 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q4 GGUF 4.1 GB 1.9 h Very slowCPU offload
81Great quality (A) · 81 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. MOSS-Image SFTOpenMOSS Q8 GGUF 4.1 GB 70.3 min Very slowCPU offload

Best Video models for the ACEMAGIC N3A 8.0 GB

Quality Model Quant Memory Speed Runs
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 67.2 min Very slowtight fit
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 4.0 GB 1.6 h Very slowCPU offload
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 4.7 GB 3.9 h Very slowtight fit · CPU offload

Best Decision models for the ACEMAGIC N3A 8.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 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. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 236 ms Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 1.9 GB 5.2 s Very slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q5_K_M 4.2 GB 34.6 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 1.9 GB 5.2 s Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. zerank-2ZeroEntropy Q5_K_M 4.2 GB 34.6 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 2.3 s Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Shieldstral 1.0 3BMistral AI Q6_K 4.4 GB 33.2 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI Q8_0 1.7 GB 3.8 s Very slow

Other products with the AMD Ryzen Embedded R2514 / R2544 NAS (8 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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