What AI models can the NVIDIA RTX Spark N1X (5120-core GPU) (24 GB) run?

Unified memory: 24.0 GB
Usable for models: 12.0 GB
Memory bandwidth: 300 GB/s
FP16 compute: 24.0 TFLOPS
Released: 2026

398 / 619 LLMs run Best: K2 Horizon 7B 54 / 60 Image models run Best: Z-Image Turbo 14 / 43 Video models run Best: LTX-Video 2B 65 / 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 24.0 GB.

More about this hardware

Maker	NVIDIA
Type	Unified-memory system on a chip
GPU share of memory	50% (what the GPU can typically be given for a model)
Chip	NVIDIA RTX Spark N1X (5120-core GPU)

Apps that run models well on the NVIDIA RTX Spark N1X (5120-core GPU) (24 GB)

Linux

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

3 products with the NVIDIA RTX Spark N1X (5120-core GPU) (24 GB)

ProArt P16 (H7607BA)ASUS · Laptop · 24, 32 or 128 GB · $7,000Product page (opens in a new tab)
ProArt P14 (H7407BA)ASUS · Laptop · 24, 32, 48 or 128 GBProduct page (opens in a new tab)
Surface Laptop UltraMicrosoft · Laptop · 24, 32, 48 or 128 GBProduct page (opens in a new tab)

Best LLMs for the NVIDIA RTX Spark N1X (5120-core GPU) (24 GB)

Quality	Model	Quant	Memory	Speed	Runs
76Great quality (A) · 76 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.	K2 Horizon 7BInstitute of Foundation Models	`Q4_K_M`	8.3 GB	40.9 tok/s	Runs great
78Great quality (A) · 78 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 12BGoogle	`Q4_K_M`	9.5 GB	30.8 tok/s	Runs great
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking.	SenseNova Loop 9B PreviewSenseTime	`Q4_K_M`	7.9 GB	38.1 tok/s	Runs great
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking.	MiMo V2.6 Distill Qwen 9BXiaomi	`Q4_K_M`	7.6 GB	39.1 tok/s	Runs great
73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking.	Ornith 1.5 9BDeepReinforce	`Q4_K_M`	7.7 GB	38.2 tok/s	Runs great
72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.5 9BAlibaba	`Q4_K_M`	7.7 GB	38.2 tok/s	Runs great
71Great quality (A) · 71 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	Ornith 1.0 9BDeepReinforce	`Q4_K_M`	7.7 GB	38.2 tok/s	Runs great
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	Nemotron 3.5 Bolt E4BNVIDIA	`Q8_0`	10.2 GB	41.7 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 85/100 (quality, fit, speed and memory use) sets the ranking.	TMax 9BAi2	`Q4_K_M`	7.3 GB	41.1 tok/s	Runs great
68Good quality (B) · 68 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 E4BGoogle	`Q8_0`	10.2 GB	41.7 tok/s	Runs great
69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.	Mellum2.1 Thinking (12B-A2.5B)JetBrains	`Q6_K`	11.6 GB	74.7 tok/s	Runs welltight fit
68Good quality (B) · 68 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.	Nanbeige4.2 3BBOSS Zhipin (Nanbeige)	`Q8_0`	7.5 GB	45.0 tok/s	Runs great

Best Image models for the NVIDIA RTX Spark N1X (5120-core GPU) (24 GB)

Quality	Model	Quant	Memory	Speed	Runs
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking.	Z-Image TurboAlibaba (Tongyi)	`Q4 GGUF`	10.1 GB	7.6 s	Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`Q4 GGUF`	10.2 GB	17 s	Runs well
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 4BBlack Forest Labs	`FP8`	10.2 GB	2.3 s	Runs great
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE-Image TurboBaidu	`Q4 GGUF`	11.3 GB	9.7 s	Runs welltight fit
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 9BBlack Forest Labs	`Q4 GGUF`	8.0 GB	5.7 s	Runs greatencoder unloaded after use
60Good quality (B) · 60 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.	Animagine XL 4.0Cagliostro Lab	`FP16`	8.9 GB	11 s	Runs great

Best Video models for the NVIDIA RTX Spark N1X (5120-core GPU) (24 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 75/100 (quality, fit, speed and memory use) sets the ranking.	LTX-Video 2BLightricks	`FP8`	10.8 GB	57 s	Runs welltight fit
44Fair quality (C) · 44 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.	CogVideoX 2BZhipu AI	`FP8`	11.0 GB	2.3 min	Runs welltight fit
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5BZhipu AI	`FP8`	9.6 GB	7.2 min	Runs wellencoder unloaded after use
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5B I2VZhipu AI	`FP8`	10.2 GB	7.2 min	Runs wellencoder unloaded after use
55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.1 T2V 1.3BAlibaba	`FP16`	8.4 GB	10.6 min	Runs wellencoder unloaded after use

Best Decision models for the NVIDIA RTX Spark N1X (5120-core GPU) (24 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`	3.0 GB	29 ms	Runs great
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3 Reranker 4BAlibaba	`Q8_0`	6.1 GB	145 ms	Runs well
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Intern-Decision 4BShanghai AI Lab	`Q8_0`	6.4 GB	95 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`	3.0 GB	29 ms	Runs great
88Excellent quality (A+) · 88 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	zerank-2ZeroEntropy	`Q8_0`	6.1 GB	145 ms	Runs well
82Great quality (A) · 82 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.	d1 3BLiquid AI	`F16`	7.8 GB	86 ms	Runs great
82Great quality (A) · 82 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.	mxbai-rerank-large v2Mixedbread	`F16`	4.7 GB	67 ms	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	Shieldstral 1.0 3BMistral AI	`Q8_0`	5.9 GB	139 ms	Runs well

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.