Products · TerraMaster · NAS
TerraMaster F4-424 Pro
- Processor
- Intel Core i3-N305 / Core 3 N355
- Memory (RAM)
- 16 or 32 GB
- Launch price
- $774
- 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 i3-N305 / Core 3 N355 | 16.0 GB | 12.0 GB | 38 GB/s | 168 of 622 | $774 |
| Intel Core i3-N305 / Core 3 N355 | 32.0 GB | 26.2 GB | 38 GB/s | 200 of 622 | — |
Specifications 32.0 GB configuration
| Maker | TerraMaster |
|---|---|
| Type | NAS |
| Processor | Intel Core i3-N305 / Core 3 N355 NAS (32 GB) |
| Memory (RAM) | 32.0 GB |
| Usable for AI models | 26.2 GB |
| Memory bandwidth | 38 GB/s |
| FP16 compute | 0.3 TFLOPS |
| Runs models on | CPU cores |
| Drive bays | 4x SATA + 2x M.2 NVMe |
| NAS system | TOS 6 |
| Containers (Docker) | Yes |
| Virtual machines | Yes |
| Memory upgrade | DDR5 SODIMM (non-ECC) · 1 slot · up to 32.0 GB per the maker · non-ECC |
| Notes | Intel Core i3-N305. CPU only, but 8 cores and up to 32 GB. The maker's blog says its x86 NAS can run a 7B model through Ollama in Docker. No independent tokens-per-second benchmark was found; memory is single channel, which limits speed. Ships with 32 GB and is named in the maker's private-AI blog post. |
| Product page | www.terra-master.com (opens in a new tab) |
Running AI on the TerraMaster F4-424 Pro
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
| App | How it installs |
|---|---|
| Ollama | In a container (Docker) |
| Open WebUI | In a container (Docker) |
AI features from TerraMaster
| Feature | What it does | Where 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 F4-424 Pro 32.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.6 35B-A3B | Q3_K_M | 20.5 GB | 12.2 tok/s | Runs well |
| 94Excellent quality (A+) · 94 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.8 27B | Q6_K | 26.0 GB | 0.7 tok/s | Very slowtight fit |
| 78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | MiniCPM-V 4.7 35B-A3B | Q3_K_M | 20.1 GB | 12.2 tok/s | Runs well |
| 78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.5 35B-A3B | Q3_K_M | 20.5 GB | 12.2 tok/s | Runs well |
| 77Great quality (A) · 77 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Nex N2 Mini (35B-A3B) | Q3_K_M | 20.1 GB | 12.2 tok/s | Runs well |
| 93Excellent quality (A+) · 93 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.6 27B | Q6_K | 26.0 GB | 0.7 tok/s | Very slowtight fit |
| 76Great quality (A) · 76 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. | KAT-Coder V2.5 Dev (35B-A3B) | Q3_K_M | 19.9 GB | 12.2 tok/s | Runs well |
| 76Great quality (A) · 76 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. | Sage-A1.5 35B-A3B | Q3_K_M | 20.5 GB | 12.2 tok/s | Runs well |
| 92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.5 27B | Q6_K | 26.0 GB | 0.7 tok/s | Very slowtight fit |
| 75Great quality (A) · 75 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. | Ornith 1.5 35B-A3B | Q3_K_M | 20.5 GB | 12.2 tok/s | Runs well |
Best Image models for the TerraMaster F4-424 Pro 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 82/100 (quality, fit, speed and memory use) sets the ranking. | Krea 2 Turbo | FP8 | 20.2 GB | 8.3 min | Very slow |
| 82Great quality (A) · 82 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. | FLUX.2 [klein] 9B | FP8 | 19.9 GB | 3.5 min | Very 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-Image | Q8 GGUF | 18.9 GB | 54.0 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 4 | NF4 | 21.8 GB | 58.7 min | Very slow |
| 78Great quality (A) · 78 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. | FLUX.2 [klein] 4B | FP16 | 18.1 GB | 2.1 min | Slow |
| 90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | FLUX 3 Image Klein | Q8 GGUF | 12.8 GB | 14.0 min | Very slow |
Best Video models for the TerraMaster F4-424 Pro 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) | FP8 | 20.3 GB | 24.2 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) | FP8 | 24.6 GB | 17.0 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) | Q4 GGUF | 21.6 GB | 42.7 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 480P | Q4 GGUF | 20.6 GB | 38.4 h | Very slow |
| 79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. | LTX-2.3 | Q4 GGUF | 24.5 GB | 17.9 h | Very slowtight fit · encoder unloaded after use |
Best Decision models for the TerraMaster F4-424 Pro 32.0 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 87/100 (quality, fit, speed and memory use) sets the ranking. | OpenAI Privacy Filter | Q8_0 | 2.4 GB | 114 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 v3.5 | Q8_0 | 3.6 GB | 2.5 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 4B | Q8_0 | 7.3 GB | 16.6 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 8B | Q8_0 | 11.7 GB | 33.8 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 8B | Q8_0 | 10.4 GB | 66.3 s | Very slow |
| 84Great quality (A) · 84 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 | Q8_0 | 3.6 GB | 2.5 s | Very 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-2 | Q8_0 | 7.3 GB | 16.6 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 Decide | Q8_0 | 1.2 GB | 1.1 s | Slow |
Other products with the Intel Core i3-N305 / Core 3 N355 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.