GPU GUIDE · NVIDIA
Best AI models for the
NVIDIA RTX 6000 Ada
The NVIDIA RTX 6000 Ada has 48.0GB of VRAM. Below are the top 30 open-source AI models that fit, ranked by composite benchmark score. Each row shows the best quantization that fits your hardware.
VRAM
48.0GB
Brand
nvidia
Models that fit
30
Generation
Professional
Top 30 models for the NVIDIA RTX 6000 Ada
01
67.1DeepSeek V4 Flash
37.0BBest fit: Q8_0 · 40.3GBCan I run it? →
02
61.8Qwen 3.6 27B
27.0BBest fit: Q8_0 · 29.7GBCan I run it? →
03
56.3Qwen3.5-27B
27.8BBest fit: Q8_0 · 30.5GBCan I run it? →
04
52.7Qwen 3.6 35B A3B
35.0BBest fit: Q8_0 · 38.2GBCan I run it? →
05
48.9Gemma 4 31B
31.0BBest fit: Q8_0 · 33.9GBCan I run it? →
06
48.8Qwen 3.5 35B A3B
35.0BBest fit: Q8_0 · 38.2GBCan I run it? →
07
42.8Gemma 4 26B A4B
26.5BBest fit: Q8_0 · 29.2GBCan I run it? →
08
36.7Devstral 2
24.0BBest fit: Q8_0 · 26.5GBCan I run it? →
09
36.4gemma 4 12B it
12.0BBest fit: fp16 · 25.0GBCan I run it? →
10
35.7Qwen 3.5 9B
9.0BBest fit: fp16 · 19.0GBCan I run it? →
11
33.5Qwen 3.5 4B
4.0BBest fit: fp16 · 9.0GBCan I run it? →
12
31.7Devstral Small 2
7.0BBest fit: fp16 · 15.0GBCan I run it? →
13
30.6Seed OSS 36B Instruct
36.2BBest fit: Q8_0 · 39.5GBCan I run it? →
14
29.1Devstral Small 2 24B Instruct 2512
24.0BBest fit: Q8_0 · 26.5GBCan I run it? →
15
27.9Qwen3 Next 80B A3B Thinking
81.3BBest fit: Q4_K_S · 47.5GBCan I run it? →
16
26.7Ministral 3 14B
14.0BBest fit: fp16 · 29.0GBCan I run it? →
17
25.0Ministral 3 8B
8.0BBest fit: fp16 · 17.0GBCan I run it? →
18
25.0Gemma 4 E2B
2.0BBest fit: f32 · 9.0GBCan I run it? →
19
24.9Nemotron 3 Nano Omni (free)
33.0BBest fit: Q8_0 · 36.1GBCan I run it? →
20
24.8GPT-OSS 20B
21.5BBest fit: fp16 · 44.0GBCan I run it? →
21
24.1Qwen3 30B A3B Thinking 2507
30.5BBest fit: Q8_0 · 33.4GBCan I run it? →
22
23.6Nemotron 3 Nano 30B A3B
31.6BBest fit: Q8_0 · 34.6GBCan I run it? →
23
22.7Qwen3 Coder 30B A3B Instruct
30.5BBest fit: Q8_0 · 33.4GBCan I run it? →
24
22.4diffusiongemma 26B A4B it
25.8BBest fit: Q8_0 · 28.4GBCan I run it? →
25
22.3QwQ 32B
32.8BBest fit: Q8_0 · 35.9GBCan I run it? →
26
22.9Qwen3 Next 80B A3B Instruct
81.3BBest fit: Q4_K_S · 47.5GBCan I run it? →
27
22.2Qwen3 VL 30B A3B Thinking
31.1BBest fit: Q8_0 · 34.0GBCan I run it? →
28
20.8Mistral Medium 3.5
70.0BBest fit: Q4_K_M · 43.4GBCan I run it? →
29
19.9Qwen3 4B Thinking 2507
4.0BBest fit: fp16 · 9.0GBCan I run it? →
30
19.8gemma 4 E4B it
8.0BBest fit: f32 · 33.0GBCan I run it? →
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FAQ — running AI on the NVIDIA RTX 6000 Ada
How many AI models can the NVIDIA RTX 6000 Ada run?
With 48.0GB of VRAM, the NVIDIA RTX 6000 Ada can run 30+ open-source models from our database, including DeepSeek V4 Flash, Qwen 3.6 27B, Qwen3.5-27B.
What's the largest LLM I can run on a NVIDIA RTX 6000 Ada?
The biggest model that fits is approximately 81.3B. Larger models would need to be quantized further or won't fit at all.
Is 48.0GB of VRAM enough for local AI?
Yes — 48.0GB comfortably runs most popular open-source models including 30B-class LLMs at Q4_K_M.