ASUS NUC 15 Pro

Hardware · Intel

What AI models can the Intel Core Ultra 200H (Arc 140T) (32 GB) run?

Unified memory
32.0 GB
Usable for models
18.2 GB
Memory bandwidth
102 GB/s
FP16 compute
9.2 TFLOPS
Released
2025
459 / 622 LLMs run Best: Gemma 4 26B-A4B 58 / 61 Image models run Best: Z-Image Turbo 21 / 43 Video models run Best: LTX-Video 2B 67 / 70 Decision models run Best: Jina Reranker v3.5

macOS lets the GPU use roughly two-thirds to three-quarters of unified memory by default, so we plan around that figure rather than the full 32.0 GB.

More about this hardware

MakerIntel
TypeUnified-memory system on a chip
GPU share of memory57% (what the GPU can typically be given for a model)
ChipIntel Core Ultra 200H (Arc 140T)

Apps that run models well on the Intel Core Ultra 200H (Arc 140T) (32 GB)

Windows

  1. llama.cppSupports Intel Arc through SYCL and Vulkan.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaIntel GPU support here is experimental (Vulkan).
  4. JanPoint-and-click: search, download and chat in one window.

Linux

  1. llama.cppSupports Intel Arc through SYCL and Vulkan.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaIntel GPU support here is experimental (Vulkan).
  4. JanPoint-and-click: search, download and chat in one window.

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

1 product with the Intel Core Ultra 200H (Arc 140T) (32 GB)

Best LLMs for the Intel Core Ultra 200H (Arc 140T) (32 GB)

Quality Model Quant Memory Speed Runs
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q4_K_M 18.2 GB 23.3 tok/s Runs welltight fit
73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. GLM-4.7 Flash (30B-A3B)Zhipu AI Q3_K_M 17.8 GB 36.5 tok/s Runs welltight fit
71Great quality (A) · 71 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Hunyuan Hy-Memory 30B-A3BTencent Q3_K_M 17.6 GB 36.5 tok/s Runs welltight fit
66Good quality (B) · 66 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. Maple Preview (20B-A1B)DeepGrove Q4_K_M 14.5 GB 53.0 tok/s Runs great
70Great quality (A) · 70 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. LFM2.5 24B-A2BLiquid AI Q4_K_M 16.8 GB 34.6 tok/s Runs welltight fit
73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Raon-1 mini Preview (30B-A4B)KRAFTON Q3_K_M 16.2 GB 26.4 tok/s Runs welltight fit
70Great quality (A) · 70 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. gpt-oss 20BOpenAI MXFP4 14.2 GB 26.0 tok/s Runs well
67Good quality (B) · 67 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. North Mini Code 1.0 (30B-A3B)Cohere Q3_K_M 17.3 GB 36.5 tok/s Runs welltight fit
74Great quality (A) · 74 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. DiffusionGemma 26B-A4B ITGoogle Q4_K_M 18.2 GB 22.2 tok/s Runs welltight fit
65Good quality (B) · 65 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q2_K 16.6 GB 45.1 tok/s Runs welltight fit
65Good quality (B) · 65 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 35B-A3BOpenBMB Q2_K 16.3 GB 45.1 tok/s Runs welltight fit
65Good quality (B) · 65 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 35B-A3BAlibaba Q2_K 16.6 GB 45.1 tok/s Runs welltight fit

Best Image models for the Intel Core Ultra 200H (Arc 140T) (32 GB)

Quality Model Quant Memory Speed Runs
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) FP8 12.6 GB 21 s Runs well
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 10.2 GB 8.4 s Runs great
89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs FP8 12.4 GB 48 s Slow
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu FP8 14.5 GB 27 s Runs well
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs FP8 11.7 GB 16 s Runs wellencoder unloaded after use
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP8 15.7 GB 38 s Runs welltight fit · encoder unloaded after use

Best Video models for the Intel Core Ultra 200H (Arc 140T) (32 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 74/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 3.5 min Runs great
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP8 15.7 GB 77.9 min 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 69/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5BZhipu AI FP8 14.3 GB 25.2 min Slow
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5B I2VZhipu AI FP8 14.9 GB 25.2 min Slow
68Good quality (B) · 68 of 100: how capable the model is at FP16, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Kandinsky 6.0 Video Lite (3B, video + audio)Sber AI FP16 14.7 GB 50.6 min Very slowencoder unloaded after use

Best Decision models for the Intel Core Ultra 200H (Arc 140T) (32 GB)

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at F16, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI F16 3.5 GB 91 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI F16 3.5 GB 91 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI F16 2.4 GB 56 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino F16 1.7 GB 35 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba F16 3.5 GB 91 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 86MMeta F16 1.2 GB 39 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-base v2Mixedbread F16 3.1 GB 75 ms Runs great
74Great quality (A) · 74 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. GLiClass ModernBERT Large v3Knowledgator F16 1.5 GB 29 ms Runs great

Best LLMs by task on this hardware Open in Model Finder

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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