Products · QNAP · NAS
QNAP TBS-h574TX
- Chips
- Intel Core i5-1240P / i5-1340P or Intel Core i5-1235U / i7-1255U
- Memory (RAM)
- 12 or 16 GB
- Released
- 2023
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 Core i5-1240P / i5-1340P · Intel Core i5-1240P / i5-1340P | 12.0 GB | 8.4 GB | 38 GB/s | 205 of 622 | — |
| Intel Core i5-1235U / i7-1255U · Intel Core i5-1235U / i7-1255U | 16.0 GB | 12.0 GB | 38 GB/s | 214 of 622 | — |
| Intel Core i5-1240P / i5-1340P · Intel Core i5-1240P / i5-1340P | 16.0 GB | 12.0 GB | 38 GB/s | 214 of 622 | — |
Specifications 12.0 GB configuration
| Maker | QNAP |
|---|---|
| Type | NAS |
| Processor | Intel Core i5-1240P / i5-1340P NAS (12 GB) · Intel Core i5-1240P / i5-1340P |
| Memory (RAM) | 12.0 GB |
| Usable for AI models | 8.4 GB |
| Memory bandwidth | 38 GB/s |
| FP16 compute | 0.5 TFLOPS |
| Runs models on | CPU cores |
| Drive bays | 5 x E1.S up to 15 mm (PCIe Gen3 x2 each); each bay ships with an adapter that takes one M.2 2280 NVMe SSD… |
| NAS system | QuTS hero |
| Containers (Docker) | Yes |
| Virtual machines | Yes |
| Memory upgrade | soldered (non-expandable) · up to 16.0 GB per the maker |
| Notes | Intel Core i5-1235U, 10C (2P+8E)/12T, 4.4GHz. Only 10 cores; up to 16 GB RAM. CPU-only inference of small models via Docker. |
| Product page | www.qnap.com (opens in a new tab) |
Running AI on the QNAP TBS-h574TX
It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 8.4 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
| App | How it installs |
|---|---|
| Ollama + Open WebUI | In a container (Docker) |
| Ollama / Open WebUI or any other LLM server image | In a container (Docker) |
| Any Linux VM running an LLM runtime | In a virtual machine |
AI features from QNAP
| Feature | What it does | Where the AI runs |
|---|---|---|
| Qsirch RAG Search (cloud LLM mode) | Natural-language search and Q&A over NAS files; retrieval runs on the NAS but the LLM is a cloud API (Gemini, OpenAI, Azure OpenAI or OpenAI-compatible). | Cloud service or another computer |
Best LLMs for the QNAP TBS-h574TX 12.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | Ling 3.0 Tiny (8B-A1.3B) | Q4_K_M | 6.3 GB | 31.5 tok/s | Runs great |
| 76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | K2 Horizon 7B | Q4_K_M | 8.0 GB | 5.1 tok/s | Slowtight fit |
| 75Great quality (A) · 75 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | MiMo V2.6 Distill Qwen 9B | Q5_K_M | 8.2 GB | 4.0 tok/s | Slowtight fit |
| 74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | SenseNova Loop 9B Preview | Q4_K_M | 7.6 GB | 4.7 tok/s | Slowtight fit |
| 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | Nemotron 3.5 Bolt E4B | Q4_K_M | 6.3 GB | 10.2 tok/s | Runs well |
| 74Great quality (A) · 74 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | Ornith 1.5 9B | Q5_K_M | 8.4 GB | 3.9 tok/s | Slowtight fit |
| 70Great quality (A) · 70 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | TMax 9B | Q4_K_M | 7.0 GB | 5.1 tok/s | Slow |
| 73Great quality (A) · 73 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.5 9B | Q5_K_M | 8.4 GB | 3.9 tok/s | Slowtight fit |
| 64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. | Gemma 4 E4B | Q4_K_M | 6.3 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 76/100 (quality, fit, speed and memory use) sets the ranking. | Mellum2.1 Thinking (12B-A2.5B) | Q3_K_M | 7.3 GB | 22.0 tok/s | Runs welltight fit |
Best Image models for the QNAP TBS-h574TX 12.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. | FLUX 3 Image Klein | FP8 | 7.9 GB | 8.1 min | Very slowtight fit · encoder unloaded after use |
| 76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | FLUX.2 [klein] 4B | FP8 | 6.2 GB | 85 s | Slowencoder unloaded after use |
| 78Great quality (A) · 78 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. | Z-Image Turbo | Q4 GGUF | 6.1 GB | 4.7 min | Very slowencoder unloaded after use |
| 78Great quality (A) · 78 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. | FLUX.2 [klein] 9B | Q4 GGUF | 8.0 GB | 3.4 min | Very slowtight fit · encoder unloaded after use |
| 79Great quality (A) · 79 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. | ERNIE-Image Turbo | Q4 GGUF | 7.4 GB | 6.0 min | Very slowtight fit · encoder unloaded after use |
| 81Great quality (A) · 81 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. | ERNIE-Image | Q4 GGUF | 7.4 GB | 41.5 min | Very slowtight fit · encoder unloaded after use |
Best Video models for the QNAP TBS-h574TX 12.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. | LTX-Video 2B | FP8 | 6.1 GB | 35.3 min | Slowencoder unloaded after use |
| 74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. | HY-OmniWeaving (8.3B, unified video) | FP8 | 7.8 GB | 15.5 h | Very slowtight fit · CPU offload |
| 53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. | Wan 2.1 T2V 1.3B | FP8 | 7.1 GB | 5.7 h | Very slowtight fit · encoder unloaded after use |
| 53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. | Wan 2.1 VACE 1.3B | FP8 | 8.0 GB | 6.1 h | Very slowtight fit · encoder unloaded after use |
| 35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. | AnimateDiff v3 (SD 1.5) | FP16 | 4.7 GB | 29.9 min | Slow |
Best Decision models for the QNAP TBS-h574TX 12.0 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 Filter | F16 | 3.8 GB | 55 ms | Runs great |
| 68Good quality (B) · 68 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. | Llama Prompt Guard 2 22M | Q8_0 | 0.7 GB | 129 ms | Runs great |
| 86Excellent quality (A+) · 86 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 v3.5 | Q8_0 | 2.1 GB | 1.0 s | Slow |
| 80Great quality (A) · 80 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. | GLiNER2.5 Decide | Q8_0 | 1.2 GB | 437 ms | Slow |
| 84Great quality (A) · 84 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. | Jina Reranker v3 | Q8_0 | 2.1 GB | 1.0 s | 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 4B | Q8_0 | 5.8 GB | 6.7 s | Very slow |
| 80Great quality (A) · 80 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. | FRIDA-Decisions | Q8_0 | 1.7 GB | 728 ms | Slow |
| 88Excellent quality (A+) · 88 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. | zerank-2 | Q8_0 | 5.8 GB | 6.7 s | Very slow |
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.