What AI models can the NVIDIA RTX A1000 run?

VRAM: 8.0 GB
Usable for models: 8.0 GB
Memory bandwidth: 192 GB/s
FP16 compute: 6.7 TFLOPS
Released: 2024

459 / 622 LLMs run Best: K2 Horizon 7B 49 / 61 Image models run Best: FLUX.2 [klein] 4B 7 / 43 Video models run Best: LTX-Video 2B 65 / 70 Decision models run Best: Jina Reranker v3.5

More about this hardware

Maker	NVIDIA
Type	Workstation / datacenter graphics card
Interface	PCIe 4.0

Apps that run models well on the NVIDIA RTX A1000

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

15 products with the NVIDIA RTX A1000

NVIDIA RTX A1000NVIDIA · Workstation card · 8 GB · $550Product page (opens in a new tab)
APEXX T4 PRO-XBOXX · Workstation · 4, 8, 16, 24, 32, 48 or 96 GBProduct page (opens in a new tab)
APEXX W4BOXX · Workstation · 4, 8, 16, 24, 32, 48 or 96 GBProduct page (opens in a new tab)
Precision 5860 Tower WorkstationDell · Workstation · 4, 8, 12, 16, 20, 24, 32, 40 or 48 GBProduct page (opens in a new tab)
Precision 7875 Tower WorkstationDell · Workstation · 4, 8, 12, 16, 20, 24, 32, 40 or 48 GBProduct page (opens in a new tab)
Precision 7960 Tower WorkstationDell · Workstation · 4, 8, 12, 16, 20, 24, 32, 40 or 48 GBProduct page (opens in a new tab)
ThinkStation P5 WorkstationLenovo · Workstation · 4, 8, 12, 16, 20, 24 or 48 GBProduct page (opens in a new tab)
ThinkStation P7 WorkstationLenovo · Workstation · 4, 8, 12, 16, 20, 24 or 48 GBProduct page (opens in a new tab)
ThinkStation P8 WorkstationLenovo · Workstation · 4, 8, 16, 20, 24, 32 or 48 GBProduct page (opens in a new tab)
ThinkStation PX WorkstationLenovo · Workstation · 4, 8, 12, 16, 20, 24, 40 or 48 GBProduct page (opens in a new tab)
Valence Workstation - VWS-172109266Exxact · Workstation · 4, 8, 20, 24, 32, 40, 48 or 96 GBProduct page (opens in a new tab)
TensorEX Rackmount Workstation - TWS-154715021Exxact · Workstation · 4, 8, 20, 24, 32, 40, 48, 94 or 96 GBProduct page (opens in a new tab)
Valence Workstation - VWS-173807702Exxact · Workstation · 4, 8, 20, 24, 32, 40, 48, 72 or 96 GBProduct page (opens in a new tab)
Valence Workstation - VWS-107355433Exxact · Workstation · 4, 8, 16, 24, 32, 48, 72 or 96 GBProduct page (opens in a new tab)
Valence Workstation - VWS-130523500Exxact · Workstation · 4, 8, 16, 20, 24, 32, 40, 48, 72 or 96 GBProduct page (opens in a new tab)

Best LLMs for the NVIDIA RTX A1000

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 85/100 (quality, fit, speed and memory use) sets the ranking.	K2 Horizon 7BInstitute of Foundation Models	`Q4_K_M`	7.7 GB	26.2 tok/s	Runs welltight fit
67Good quality (B) · 67 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.	Nanbeige4.2 3BBOSS Zhipin (Nanbeige)	`Q6_K`	5.9 GB	39.2 tok/s	Runs great
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.	Nemotron 3.5 Bolt E4BNVIDIA	`Q4_K_M`	6.0 GB	52.4 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 84/100 (quality, fit, speed and memory use) sets the ranking.	MiMo V2.6 Distill Qwen 9BXiaomi	`Q4_K_M`	7.0 GB	25.0 tok/s	Runs welltight fit
64Good quality (B) · 64 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.	Gemma 4 E4BGoogle	`Q4_K_M`	6.0 GB	52.4 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 84/100 (quality, fit, speed and memory use) sets the ranking.	SenseNova Loop 9B PreviewSenseTime	`Q4_K_M`	7.4 GB	24.4 tok/s	Runs welltight fit
67Good quality (B) · 67 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.	Nemotron Labs Dory 1.0 4BNVIDIA	`Q6_K`	4.7 GB	41.1 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 83/100 (quality, fit, speed and memory use) sets the ranking.	TMax 9BAi2	`Q4_K_M`	6.7 GB	26.3 tok/s	Runs well
73Great quality (A) · 73 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.	Ornith 1.5 9BDeepReinforce	`Q4_K_M`	7.2 GB	24.4 tok/s	Runs welltight fit
72Great quality (A) · 72 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.	Qwen3.5 9BAlibaba	`Q4_K_M`	7.2 GB	24.4 tok/s	Runs welltight fit
62Good quality (B) · 62 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.	Gemma 4 E2BGoogle	`Q8_0`	6.5 GB	52.2 tok/s	Runs great
65Good quality (B) · 65 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.	Spark-X2.6 4BSparkLLM	`Q6_K`	4.7 GB	39.8 tok/s	Runs great

Best Image models for the NVIDIA RTX A1000

Quality	Model	Quant	Memory	Speed	Runs
77Great quality (A) · 77 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 4BBlack Forest Labs	`Q8 GGUF`	6.4 GB	7.9 s	Runs greatencoder in RAM
56Good quality (B) · 56 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.	DreamShaper XL v2 TurboLykon	`FP8`	5.6 GB	7.7 s	Runs great
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	Z-Image TurboAlibaba (Tongyi)	`Q4 GGUF`	6.1 GB	21 s	Runs wellencoder in RAM
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`Q4 GGUF`	5.7 GB	47 s	Slowencoder in RAM
52Fair quality (C) · 52 of 100: how capable the model is at FP8, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.	SDXL-Lightning (4-step)ByteDance	`FP8`	5.6 GB	4.1 s	Runs great
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE-Image TurboBaidu	`Q4 GGUF`	7.4 GB	27 s	Runs welltight fit · encoder in RAM

Best Video models for the NVIDIA RTX A1000

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 72/100 (quality, fit, speed and memory use) sets the ranking.	LTX-Video 2BLightricks	`FP8`	6.1 GB	2.6 min	Runs greatencoder in RAM
35Basic quality (D) · 35 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.	AnimateDiff v3 (SD 1.5)Shanghai AI Lab	`FP16`	4.7 GB	2.2 min	Runs great
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 2BZhipu AI	`FP8`	6.2 GB	6.2 min	Runs wellencoder in RAM
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.1 T2V 1.3BAlibaba	`FP8`	7.1 GB	24.9 min	Slowtight fit · encoder in RAM
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5BZhipu AI	`FP8`	5.9 GB	23.1 min	SlowCPU offload

Best Decision models for the NVIDIA RTX A1000

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`	2.4 GB	79 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`	2.4 GB	79 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	58 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	37 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`	2.4 GB	79 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	41 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`	2.0 GB	65 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	31 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.