TerraMaster F4-424 Max

Products · · NAS

TerraMaster F4-424 Max

Processor
Intel Core i5-1235U / i7-1255U
Memory (RAM)
8 or 64 GB
Launch price
$900
Released
2024

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 Core i5-1235U / i7-1255U 8.0 GB 5.2 GB 38 GB/s 177 of 622 $900
Intel Core i5-1235U / i7-1255U · upgraded to the maker's maximum 64.0 GB 54.4 GB 38 GB/s 257 of 622 —

Specifications 64.0 GB configuration

MakerTerraMaster
TypeNAS
ProcessorIntel Core i5-1235U / i7-1255U NAS (64 GB) · upgraded to the maker's maximum
Memory (RAM)64.0 GB
Usable for AI models54.4 GB
Memory bandwidth38 GB/s
FP16 compute0.4 TFLOPS
Runs models onCPU cores
Drive bays4x SATA + 2x M.2 NVMe (PCIe 4.0 x4)
NAS systemTOS 7
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR5 SODIMM (non-ECC) · 2 slots · up to 64.0 GB per the maker · non-ECC
NotesIntel Core i5-1235U. CPU only (12th/13th-gen Core U-series) with two memory slots up to 64 GB, so 7B-14B quantised models fit after a memory upgrade. No GPU support statement and no tokens-per-second benchmark was found.
Product pagewww.terra-master.com (opens in a new tab)

Running AI on the TerraMaster F4-424 Max

Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 54.4 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

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
OpenClaw AI agent (built into TOS 7) Natural-language control of NAS functions. The maker setup guide has the user pick a model provider (such as OpenAI) and paste an API key, so the language model runs remotely by default, not on the NAS. Cloud service or another computer

Best LLMs for the TerraMaster F4-424 Max 64.0 GB

Quality Model Quant Memory Speed Runs
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q6_K 34.6 GB 10.2 tok/s Runs well
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 35B-A3BAlibaba Q6_K 34.6 GB 10.2 tok/s Runs well
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 35B-A3BOpenBMB Q6_K 34.0 GB 10.2 tok/s Runs well
89Excellent quality (A+) · 89 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Flint (40B-A2.5B)Recursive Q6_K 37.8 GB 12.2 tok/s Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Nex N2 Mini (35B-A3B)Nex-AGI Q6_K 33.9 GB 10.2 tok/s Runs well
90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Sage-A1.5 35B-A3BInternScience Q6_K 34.6 GB 10.2 tok/s Runs well
89Excellent quality (A+) · 89 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 35B-A3BDeepReinforce Q6_K 34.6 GB 10.2 tok/s Runs well
90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. KAT-Coder V2.5 Dev (35B-A3B)Kuaishou Q6_K 33.5 GB 10.2 tok/s Runs well
88Excellent quality (A+) · 88 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Apodex 1.1 Mini (35B-A3B)Apodex Q6_K 34.6 GB 10.2 tok/s Runs well
88Excellent quality (A+) · 88 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 35B-A3BDeepReinforce Q6_K 34.6 GB 10.2 tok/s Runs well

Best Image models for the TerraMaster F4-424 Max 64.0 GB

Quality Model Quant Memory Speed Runs
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP16 37.4 GB 7.8 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen-Image 2.1Alibaba Q8 GGUF 41.6 GB 2.1 h Very slow
84Great quality (A) · 84 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. FLUX.2 [klein] 9BBlack Forest Labs FP16 37.1 GB 3.3 min Very slow
89Excellent quality (A+) · 89 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. Qwen-Image 2512Alibaba Q8 GGUF 36.5 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 80/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu FP16 34.0 GB 39.7 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. Fibo 2.0 DevBria AI FP16 27.7 GB 40.6 min Very slow

Best Video models for the TerraMaster F4-424 Max 64.0 GB

Quality Model Quant Memory Speed Runs
85Excellent quality (A+) · 85 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. LTX-2.3Lightricks Q8 GGUF 45.6 GB 13.8 h Very slow
87Excellent quality (A+) · 87 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. LTX-2.5 (22B, video + audio)Lightricks Q8 GGUF 49.8 GB 3.2 h Very slowtight fit
85Excellent quality (A+) · 85 of 100: how capable the model is at FP16, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP16 46.0 GB 21.7 h Very slow
85Excellent quality (A+) · 85 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. Wan 2.2 I2V A14BAlibaba Q8 GGUF 39.3 GB 55.4 h Very slow
85Excellent quality (A+) · 85 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. Wan 2.2 T2V A14BAlibaba Q8 GGUF 39.3 GB 55.4 h Very slow

Best Decision models for the TerraMaster F4-424 Max 64.0 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 FilterOpenAI F16 3.8 GB 69 ms Runs great
86Excellent quality (A+) · 86 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 v3.5Jina AI Q8_0 5.8 GB 1.3 s Slow
80Great quality (A) · 80 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. GLiNER2.5 DecideFastino Q8_0 1.2 GB 561 ms Slow
68Good quality (B) · 68 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. Llama Prompt Guard 2 22MMeta Q8_0 0.7 GB 165 ms Runs well
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 4BAlibaba Q8_0 9.5 GB 8.6 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 5.8 GB 1.3 s 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 13.9 GB 17.5 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. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 34.1 s Very slow

Other products with the Intel Core i5-1235U / i7-1255U NAS (64 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?