TerraMaster U16-722-2224

Products · · NAS

TerraMaster U16-722-2224

Processor
Intel Xeon E-2100 / E-2200
Memory (RAM)
8 or 128 GB
Launch price
$3,504
Released
2021

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
Intel Xeon E-2100 / E-2200 8.0 GB 5.2 GB 43 GB/s 150 of 622 $3,504
Intel Xeon E-2100 / E-2200 · upgraded to the maker's maximum 128 GB 113 GB 43 GB/s 210 of 622 —

Specifications 128 GB configuration

MakerTerraMaster
TypeNAS
ProcessorIntel Xeon E-2100 / E-2200 NAS (128 GB) · upgraded to the maker's maximum
Memory (RAM)128 GB
Usable for AI models113 GB
Memory bandwidth43 GB/s
FP16 compute0.3 TFLOPS
Runs models onCPU cores
Drive bays16x SATA (rackmount)
NAS systemTOS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 (module type and ECC not published) · 4 slots · up to 128 GB per the maker
Graphics card optionsPCIe: 2x PCIe 3.0 x8 (lane width per NAScompares listing; the maker says only "two PCI-E 3.0 slots" for 10GbE and….
NotesIntel Xeon E-2224G (store text: "Xeon 2224 G 3.5Ghz quad-core"; a reviewer listing says Xeon E-2224 3.4 GHz). CPU only as sold: 4-core Xeon E with 8 GB. Memory can go to 128 GB, so mid-size models fit after an upgrade, but the maker does not state GPU support for the PCIe slots and publishes no slot width or power details.
Product pagewww.terra-master.com (opens in a new tab)

Running AI on the TerraMaster U16-722-2224

It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 113 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 TerraMaster U16-722-2224 128 GB

Quality Model Quant Memory Speed Runs
84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. gpt-oss 120BOpenAI MXFP4 76.5 GB 7.4 tok/s Slow
89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Super VL 120B-A12BNVIDIA Q4_K_M 85.6 GB 3.0 tok/s Slow
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 122B-A10BDeepReinforce Q4_K_M 86.1 GB 3.6 tok/s Slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 122B-A10BAlibaba Q4_K_M 86.1 GB 3.6 tok/s Slow
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Kolibri 1 (78B-A3.5B)Aleph Alpha Q4_K_M 57.4 GB 10.2 tok/s Runs well
89Excellent quality (A+) · 89 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt 74B-A9BNVIDIA Q5_K_M 62.9 GB 3.3 tok/s Slow
83Great quality (A) · 83 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Laguna S 2.1 (118B-A8B)Poolside Q5_K_M 94.7 GB 3.7 tok/s Slow
81Great quality (A) · 81 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 Flash Next (125B-A6B)Alibaba Q3_K_M 98.0 GB 7.6 tok/s Slowtight fit
81Great quality (A) · 81 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Qwen3-Next 80B-A3B ThinkingAlibaba Q4_K_M 59.4 GB 11.7 tok/s Runs well
81Great quality (A) · 81 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Coder Next (80B-A3B)Alibaba Q4_K_M 58.4 GB 11.7 tok/s Runs well

Best Image models for the TerraMaster U16-722-2224 128 GB

Quality Model Quant Memory Speed Runs
91Excellent quality (A+) · 91 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. MiniMax H3 ImageMiniMax FP8 72.0 GB 18.2 min Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Cosmos3-Super Text2Image (64B)NVIDIA FP8 69.1 GB 73.0 min Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. HunyuanImage 3.0 (80B-A13B)Tencent FP8 86.9 GB 1.8 h Very slow
91Excellent quality (A+) · 91 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.2 [dev]Black Forest Labs Q8 GGUF 61.9 GB 83.9 min Very slow
93Excellent quality (A+) · 93 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Qwen-Image 2.1Alibaba FP16 57.0 GB 2.0 h Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Qwen-Image 2512Alibaba FP16 63.8 GB 3.0 h Very slow

Best Video models for the TerraMaster U16-722-2224 128 GB

Quality Model Quant Memory Speed Runs
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.5 (22B, video + audio)Lightricks FP16 82.5 GB 3.1 h Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Kandinsky 6.0 Pro (29B, video + audio)Sber AI FP16 85.4 GB 99.4 h Very slow
86Excellent quality (A+) · 86 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.3Lightricks FP16 75.4 GB 13.5 h Very slow
89Excellent quality (A+) · 89 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. MiniMax H3 (33B, video + audio)MiniMax Q8 GGUF 68.2 GB 40.4 h Very slow
82Great quality (A) · 82 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. LTX-2 (19B, video + audio)Lightricks FP16 75.4 GB 13.5 h Very slow

Best Decision models for the TerraMaster U16-722-2224 128 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 88/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 97 ms Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 10.5 GB 2.1 s Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q8_0 14.2 GB 13.9 s Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 8BAlibaba Q8_0 18.6 GB 28.4 s Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 55.7 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 10.5 GB 2.1 s Very slow
80Great quality (A) · 80 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. GLiNER2.5 DecideFastino Q8_0 1.2 GB 913 ms Slow
88Excellent quality (A+) · 88 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. zerank-2ZeroEntropy Q8_0 14.2 GB 13.9 s Very slow

Other products with the Intel Xeon E-2100 / E-2200 NAS (128 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.

Was this page helpful?