RTX5000ADA32GB

32 GB VRAM0 providers0 offerings0 regions

The RTX5000ADA32GB features 32 GB of memory.

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Hardware specifications

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Memory

32 GB

GDDR7

What LLMs fit? ↓

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Provider	Count	vCPU	RAM	Region	Per GPU hour	Total/hr	Action
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LLMs that fit on the RTX5000ADA32GB

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 32 GB per GPU. Showing the 12 largest that fit.

Model	Parameters	16-bit	8-bit	4-bit
Qwen3.6 35B-A3B Alibaba	35B 3B active	86 GB Too large	47 GB Too large	28 GB 1× · 4.4 GB free
Qwen3 32B Alibaba	32.8B	79 GB Too large	43 GB Too large	25 GB 1× · 6.8 GB free
Gemma 4 31B Google	31.3B	75 GB Too large	41 GB Too large	24 GB 1× · 8 GB free
GLM-4.7 Flash Z.ai	31.2B	75 GB Too large	41 GB Too large	24 GB 1× · 8 GB free
Qwen3.6 27B Alibaba	27.8B	67 GB Too large	37 GB Tight on 1× · 4% spare	21 GB 1× · 11 GB free
Mistral Small 3.2 24B Mistral AI	24B	58 GB Too large	32 GB Barely fits on 1×	18 GB 1× · 14 GB free
gpt-oss-20b OpenAI	21B 3.6B active	— Not released	— Not released	17 GB 1× · 15 GB free
Gemma 3 12B Google	12.2B	29 GB 1× · 2.8 GB free	16 GB 1× · 16 GB free	9.4 GB 1× · 23 GB free
Granite 4.1 8B IBM	8.8B	21 GB 1× · 11 GB free	12 GB 1× · 20 GB free	6.8 GB 1× · 25 GB free
Qwen3 8B Alibaba	8.2B	20 GB 1× · 12 GB free	11 GB 1× · 21 GB free	6.3 GB 1× · 26 GB free
Llama 3.1 8B Instruct Meta	8B	19 GB 1× · 13 GB free	11 GB 1× · 21 GB free	6.2 GB 1× · 26 GB free
Mistral 7B Instruct v0.3 Mistral AI	7.2B	17 GB 1× · 15 GB free	9.6 GB 1× · 22 GB free	5.6 GB 1× · 26 GB free

Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this

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Frequently asked questions

How much VRAM does the RTX5000ADA32GB have?

The RTX5000ADA32GB comes with 32 GB of VRAM, which determines the largest models and batch sizes it can hold in memory for training and inference.

Which LLMs can I run on the RTX5000ADA32GB?

With 32 GB of VRAM, a single RTX5000ADA32GB can serve models such as Qwen3.6 35B-A3B, Qwen3 32B, Gemma 4 31B, GLM-4.7 Flash. The table above lists the estimated VRAM for each model at 16-bit, 8-bit and 4-bit precision, including the multi-GPU configurations needed for larger models.