What AI models can the NVIDIA A800 40GB Active run?

VRAM: 40.0 GB
Usable for models: 40.0 GB
Memory bandwidth: 1,555 GB/s
FP16 compute: 19.5 TFLOPS
Released: 2023

522 / 622 LLMs run Best: Nanbeige4.3 33B 61 / 61 Image models run Best: ERNIE-Image Turbo 42 / 43 Video models run Best: LTX-Video 13B 0.9.8 (distilled) 69 / 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 A800 40GB Active

Linux

vLLMThe full model fits in GPU memory at 8-bit, so it can batch many requests: best for serving a team or an app.
OllamaOne command with Ollama’s own build of this model.
LM StudioPoint-and-click: search, download and chat in one window.
SGLangThe full model fits in GPU memory at 8-bit, so it can batch many requests: best for serving a team or an app.

Windows

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

9 products with the NVIDIA A800 40GB Active

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 Rack WorkstationDell · Workstation · 4, 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 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-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 A800 40GB Active

Quality	Model	Quant	Memory	Speed	Runs
94Excellent quality (A+) · 94 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 97/100 (quality, fit, speed and memory use) sets the ranking.	Nanbeige4.3 33BBOSS Zhipin (Nanbeige)	`Q6_K`	31.5 GB	40.0 tok/s	Runs great
94Excellent quality (A+) · 94 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 97/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.8 27BAlibaba	`Q6_K`	25.9 GB	47.7 tok/s	Runs great
93Excellent quality (A+) · 93 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.6 27BAlibaba	`Q6_K`	25.9 GB	47.7 tok/s	Runs great
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.6 35B-A3BAlibaba	`Q6_K`	32.2 GB	170 tok/s	Runs great
92Excellent quality (A+) · 92 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 26B-A4BGoogle	`Q8_0`	30.4 GB	130 tok/s	Runs great
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	MiniCPM-V 4.7 35B-A3BOpenBMB	`Q6_K`	31.6 GB	170 tok/s	Runs great
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.5 35B-A3BAlibaba	`Q6_K`	32.2 GB	170 tok/s	Runs great
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.5 27BAlibaba	`Q6_K`	25.9 GB	47.7 tok/s	Runs great
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking.	Muse Glimmer 30BMeta	`Q6_K`	27.1 GB	44.5 tok/s	Runs great
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking.	Nex N2 Mini (35B-A3B)Nex-AGI	`Q6_K`	31.6 GB	170 tok/s	Runs great
90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 31BGoogle	`Q6_K`	29.9 GB	42.4 tok/s	Runs great
90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking.	KAT-Coder V2.5 Dev (35B-A3B)Kuaishou	`Q6_K`	31.2 GB	170 tok/s	Runs great

Best Image models for the NVIDIA A800 40GB Active

Quality	Model	Quant	Memory	Speed	Runs
85Excellent quality (A+) · 85 of 100: how capable the model is at FP16, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE-Image TurboBaidu	`FP16`	26.4 GB	9.4 s	Runs great
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	Krea 2 TurboKrea	`FP8`	20.2 GB	11 s	Runs great
84Great quality (A) · 84 of 100: how capable the model is at FP16, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking.	Z-Image TurboAlibaba (Tongyi)	`FP16`	22.7 GB	7.4 s	Runs great
91Excellent quality (A+) · 91 of 100: how capable the model is at FP16, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`FP16`	22.4 GB	17 s	Runs well
83Great quality (A) · 83 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 9BBlack Forest Labs	`Q8 GGUF`	20.5 GB	6.1 s	Runs great
87Excellent quality (A+) · 87 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.	Qwen-Image 2.1 TurboAlibaba	`FP8`	30.8 GB	31 s	Runs well

Best Video models for the NVIDIA A800 40GB Active

Quality	Model	Quant	Memory	Speed	Runs
66Good quality (B) · 66 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.	LTX-Video 13B 0.9.8 (distilled)Lightricks	`FP8`	30.1 GB	2.7 min	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.	LTX-2.5 (22B, video + audio)Lightricks	`FP8`	35.2 GB	4.2 min	Runs welltight fit · encoder in RAM
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.	Bernini-R A14B (video generation + editing)ByteDance	`FP8`	26.0 GB	31.9 min	Slow
79Great quality (A) · 79 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.	LTX-2.3Lightricks	`Q4 GGUF`	36.7 GB	23.6 min	Slowtight fit
84Great quality (A) · 84 of 100: how capable the model is at FP8, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.2 I2V A14BAlibaba	`FP8`	38.3 GB	70.9 min	Very slowtight fit

Best Decision models for the NVIDIA A800 40GB Active

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`	4.0 GB	27 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.	Intern-Decision 4BShanghai AI Lab	`F16`	11.7 GB	97 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`	4.0 GB	27 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`	7.2 GB	155 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`	8.9 GB	68 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`	5.7 GB	64 ms	Runs great
88Excellent quality (A+) · 88 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.	zerank-2ZeroEntropy	`Q8_0`	7.2 GB	155 ms	Runs well
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`	6.9 GB	148 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.