RTXPRO600096GB

96 GB VRAM0 providers0 offerings0 regions

The RTXPRO600096GB features 96 GB of memory.

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Hardware specifications

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Memory

96 GB

What LLMs fit? ↓

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LLMs that fit on the RTXPRO600096GB

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 96 GB per GPU. Showing the 12 largest that fit.

Model	Parameters	16-bit	8-bit	4-bit
Laguna-S 2.1 Poolside	118B 8B active	282 GB Too large	155 GB Too large	90 GB 1× · 5.7 GB free
gpt-oss-120b OpenAI	117B 5.1B active	— Not released	— Not released	78 GB 1× · 18 GB free
Qwen3.6 35B-A3B Alibaba	35B 3B active	86 GB 1× · 9.7 GB free	47 GB 1× · 49 GB free	28 GB 1× · 68 GB free
Qwen3 32B Alibaba	32.8B	79 GB 1× · 17 GB free	43 GB 1× · 53 GB free	25 GB 1× · 71 GB free
Gemma 4 31B Google	31.3B	75 GB 1× · 21 GB free	41 GB 1× · 55 GB free	24 GB 1× · 72 GB free
GLM-4.7 Flash Z.ai	31.2B	75 GB 1× · 21 GB free	41 GB 1× · 55 GB free	24 GB 1× · 72 GB free
Qwen3.6 27B Alibaba	27.8B	67 GB 1× · 29 GB free	37 GB 1× · 59 GB free	21 GB 1× · 75 GB free
Mistral Small 3.2 24B Mistral AI	24B	58 GB 1× · 38 GB free	32 GB 1× · 64 GB free	18 GB 1× · 78 GB free
gpt-oss-20b OpenAI	21B 3.6B active	— Not released	— Not released	17 GB 1× · 79 GB free
Gemma 3 12B Google	12.2B	29 GB 1× · 67 GB free	16 GB 1× · 80 GB free	9.4 GB 1× · 87 GB free
Granite 4.1 8B IBM	8.8B	21 GB 1× · 75 GB free	12 GB 1× · 84 GB free	6.8 GB 1× · 89 GB free
Qwen3 8B Alibaba	8.2B	20 GB 1× · 76 GB free	11 GB 1× · 85 GB free	6.3 GB 1× · 90 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 RTXPRO600096GB have?

The RTXPRO600096GB comes with 96 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 RTXPRO600096GB?

With 96 GB of VRAM, a single RTXPRO600096GB can serve models such as Laguna-S 2.1, gpt-oss-120b, Qwen3.6 35B-A3B, Qwen3 32B. 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.