TerraMaster U8-423

Products · · NAS

TerraMaster U8-423

Processor
Intel Celeron N5105 / N5095
Memory (RAM)
4 or 32 GB
Launch price
$1,100
Released
2022

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 Celeron N5105 / N5095 4.0 GB 2.0 GB 24 GB/s 52 of 622 $1,100
Intel Celeron N5105 / N5095 · upgraded to the maker's maximum 32.0 GB 26.2 GB 24 GB/s 72 of 622 —

Specifications 4.0 GB configuration

MakerTerraMaster
TypeNAS
ProcessorIntel Celeron N5105 / N5095 NAS (4 GB)
Memory (RAM)4.0 GB
Usable for AI models2.0 GB
Memory bandwidth24 GB/s
FP16 compute0.1 TFLOPS
Runs models onCPU cores
Drive bays8x SATA + 1x M.2 NVMe (rackmount)
NAS systemTOS 6
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 SODIMM (non-ECC) · 2 slots · up to 32.0 GB per the maker · non-ECC
NotesIntel Celeron N5095. CPU only: 4-core low-power chip, no NPU and no GPU slot. Ollama in Docker is the maker's suggested route; expect small models (1-4B, quantised) at slow speeds. No tokens-per-second benchmark was found for this model. Ships with 4 GB, so a memory upgrade is needed first.
Product pagewww.terra-master.com (opens in a new tab)

Running AI on the TerraMaster U8-423

It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 2.0 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

AI features from TerraMaster

FeatureWhat it doesWhere the AI runs
Terra Photos (TerraMaster Photos) Photo library with face and scene recognition; the maker says the AI processing uses a local model on the NAS. This is an image classifier, not a chat model. On the NAS

Best LLMs for the TerraMaster U8-423 4.0 GB

Quality Model Quant Memory Speed Runs
39Basic quality (D) · 39 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. PaddleOCR-VL 1.6 0.9BBaidu Q4_K_M 1.5 GB 12.5 tok/s Runs well
39Basic quality (D) · 39 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. LFM3 1.7BLiquid AI Q2_K 1.6 GB 11.4 tok/s Runs well
35Basic quality (D) · 35 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-OCR 1.0 1.3BOpenBMB Q3_K_M 1.5 GB 12.0 tok/s Runs well
35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. LFM3-VL 2BLiquid AI Q2_K 1.6 GB 10.3 tok/s Runs well
34Basic quality (D) · 34 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 1BOpenBMB Q4_K_M 1.6 GB 11.1 tok/s Runs well
33Basic quality (D) · 33 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 1BOpenBMB Q3_K_M 1.6 GB 10.0 tok/s Runs well
30Basic quality (D) · 30 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. LFM2.5 1.2B InstructLiquid AI Q4_K_M 1.6 GB 10.3 tok/s Runs well
33Basic quality (D) · 33 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 2BAlibaba Q3_K_M 2.0 GB 6.8 tok/s Slowtight fit
28Basic quality (D) · 28 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. TMax 2BAi2 Q2_K 1.6 GB 10.5 tok/s Runs well
24Basic quality (D) · 24 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 0.8BAlibaba Q4_K_M 1.4 GB 13.8 tok/s Runs well

Best Image models for the TerraMaster U8-423 4.0 GB

Quality Model Quant Memory Speed Runs
39Basic quality (D) · 39 of 100: how capable the model is at FP8, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. SDXL TurboStability AI FP8 1.6 GB 71 s SlowCPU offload
42Fair quality (C) · 42 of 100: how capable the model is at FP16, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking. Realistic Vision V5.1SG161222 FP16 1.3 GB 10.6 min Very slowCPU offload
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking. SD TurboStability AI FP16 1.3 GB 42 s SlowCPU offload
40Fair quality (C) · 40 of 100: how capable the model is at FP16, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking. DreamShaper 8Lykon FP16 1.3 GB 10.6 min Very slowCPU offload
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. Stable Diffusion 1.5Stability AI / Runway FP16 1.3 GB 10.6 min Very slowCPU offload
30Basic quality (D) · 30 of 100: how capable the model is at FP16, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. LCM DreamShaper v7Tsinghua (LCM) FP16 1.3 GB 2.2 min SlowCPU offload

Best Video models for the TerraMaster U8-423 4.0 GB

None of the video models in our catalog fit in this much memory.

Best Decision models for the TerraMaster U8-423 4.0 GB

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 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 v3.5Jina AI Q8_0 1.6 GB 17.2 s Very slow
84Great quality (A) · 84 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. Jina Reranker v3Jina AI Q8_0 1.6 GB 17.2 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 7.6 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI Q8_0 1.7 GB 12.7 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba Q8_0 1.6 GB 17.2 s Very slow
76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 86MMeta Q8_0 1.0 GB 8.7 s Very slow
79Great quality (A) · 79 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2Mixedbread Q5_K_M 1.9 GB 44.0 s Very slowtight fit
76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-base v2Mixedbread Q8_0 1.3 GB 14.0 s Very slow

Other products with the Intel Celeron N5105 / N5095 NAS (4 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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