What AI models can the NVIDIA RTX 4000 Ada Generation Laptop GPU run?

VRAM: 12.0 GB
Usable for models: 12.0 GB
Memory bandwidth: 432 GB/s
FP16 compute: 33.6 TFLOPS
Released: 2023

477 / 621 LLMs run Best: K2 Horizon 7B 54 / 61 Image models run Best: FLUX 3 Image Klein 14 / 43 Video models run Best: LTX-Video 2B 68 / 70 Decision models run Best: Qwen3 Reranker 4B

More about this hardware

Maker	NVIDIA
Type	Laptop GPU (soldered memory)
Interface	PCIe 4.0

Apps that run models well on the NVIDIA RTX 4000 Ada Generation Laptop GPU

Windows

Linux

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

5 products with the NVIDIA RTX 4000 Ada Generation Laptop GPU

Precision 5690 WorkstationDell · Laptop · 6, 8, 12 or 16 GBProduct page (opens in a new tab)
Precision 7680 WorkstationDell · Laptop · 6, 8, 12 or 16 GBProduct page (opens in a new tab)
Precision 7780 WorkstationDell · Laptop · 6, 8, 12 or 16 GBProduct page (opens in a new tab)
ZBook Fury 16 G11HP · Laptop · 6, 8, 12 or 16 GBProduct page (opens in a new tab)
ThinkPad P16 Gen 2Lenovo · Laptop · 4, 6, 8, 12 or 16 GBProduct page (opens in a new tab)

Best LLMs for the NVIDIA RTX 4000 Ada Generation Laptop GPU

Quality	Model	Quant	Memory	Speed	Runs
79Great quality (A) · 79 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking.	K2 Horizon 7BInstitute of Foundation Models	`Q6_K`	9.8 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 90/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 12BGoogle	`Q4_K_M`	9.2 GB	44.3 tok/s	Runs great
77Great quality (A) · 77 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	MiMo V2.6 Distill Qwen 9BXiaomi	`Q6_K`	9.2 GB	39.1 tok/s	Runs great
77Great quality (A) · 77 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	SenseNova Loop 9B PreviewSenseTime	`Q6_K`	9.6 GB	38.1 tok/s	Runs great
76Great quality (A) · 76 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.	Ornith 1.5 9BDeepReinforce	`Q6_K`	9.4 GB	38.1 tok/s	Runs great
75Great quality (A) · 75 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 9BAlibaba	`Q6_K`	9.4 GB	38.1 tok/s	Runs great
74Great quality (A) · 74 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.	Ornith 1.0 9BDeepReinforce	`Q6_K`	9.4 GB	38.1 tok/s	Runs great
73Great quality (A) · 73 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.	TMax 9BAi2	`Q6_K`	8.8 GB	41.1 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`	9.8 GB	60.0 tok/s	Runs great
69Good quality (B) · 69 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.	UI-Mate 9BTencent	`Q6_K`	9.2 GB	39.1 tok/s	Runs great
69Good quality (B) · 69 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.	UI-Venus 2 9BAnt Group (inclusionAI)	`Q6_K`	9.2 GB	39.1 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`	9.8 GB	60.0 tok/s	Runs great

Best Image models for the NVIDIA RTX 4000 Ada Generation Laptop GPU

Quality	Model	Quant	Memory	Speed	Runs
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`Q4 GGUF`	10.2 GB	13 s	Runs well
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	5.9 s	Runs great
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	1.8 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	7.5 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	4.5 s	Runs greatencoder in RAM
62Good quality (B) · 62 of 100: how capable the model is at FP16, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.	Juggernaut XL v9RunDiffusion	`FP16`	8.9 GB	8.8 s	Runs great

Best Video models for the NVIDIA RTX 4000 Ada Generation Laptop GPU

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	44 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	1.8 min	Runs welltight fit
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5BZhipu AI	`FP8`	9.6 GB	5.6 min	Runs wellencoder in RAM
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5B I2VZhipu AI	`FP8`	10.2 GB	5.6 min	Runs wellencoder in RAM
55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.1 T2V 1.3BAlibaba	`FP16`	8.4 GB	8.2 min	Runs wellencoder in RAM

Best Decision models for the NVIDIA RTX 4000 Ada Generation Laptop GPU

Quality	Model	Quant	Memory	Speed	Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3 Reranker 4BAlibaba	`Q8_0`	5.8 GB	104 ms	Runs great
88Excellent quality (A+) · 88 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking.	zerank-2ZeroEntropy	`Q8_0`	5.8 GB	104 ms	Runs great
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`	2.6 GB	22 ms	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Shieldstral 1.0 3BMistral AI	`Q8_0`	5.5 GB	100 ms	Runs great
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`	6.1 GB	69 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`	2.6 GB	22 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.	d1 3BLiquid AI	`F16`	7.5 GB	62 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`	4.3 GB	49 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.