The NVIDIA RTX PRO 6000 CC is an enterprise-class GPU built on the Blackwell architecture, featuring 96 GB of memory with 1,597 GB/s of memory bandwidth and a 600 W TDP. It delivers 120 TFLOPS of FP32 performance. Currently available from 1 provider starting at $1.93/GPU/hour, with a market median of $1.93/GPU/hour across 1 configurations.
Hardware specifications
Same across all providers
Median price across all providers
1 offering from 1 providers
Sorted by price ascending. Compare configurations side-by-side.
LLMs that fit on the NVIDIA RTX PRO 6000 CC
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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