The NVIDIA RTX PRO 4500 is an enterprise-class GPU built on the Blackwell architecture, featuring 32 GB of memory. Currently available from 3 providers starting at $0.36/GPU/hour, with a market median of $1.06/GPU/hour across 8 configurations.
Hardware specifications
Same across all providers
Median price across all providers
3 offerings from 3 providers
Sorted by price ascending. Compare configurations side-by-side.
LLMs that fit on the NVIDIA RTX PRO 4500
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 |
|---|---|---|---|---|
| DeepSeek V4 Flash DeepSeek | 284B | — Not released | — Not released | 192 GB 8× · 64 GB free |
| Solar Open2 250B Upstage | 250B 15B active | 601 GB Too large | 330 GB Too large | 192 GB 8× · 64 GB free |
| Qwen3 235B-A22B Alibaba | 235B 22B active | 564 GB Too large | 310 GB Too large | 181 GB 8× · 75 GB free |
| Laguna-S 2.1 Poolside | 118B 8B active | 282 GB Tight on 8× · 8% spare | 155 GB 8× · 101 GB free | 90 GB 4× · 38 GB free |
| gpt-oss-120b OpenAI | 117B 5.1B active | — Not released | — Not released | 78 GB 4× · 50 GB free |
| Qwen3.6 35B-A3B Alibaba | 35B 3B active | 86 GB 4× · 42 GB free | 47 GB 2× · 17 GB free | 28 GB 1× · 4.4 GB free |
| Qwen3 32B Alibaba | 32.8B | 79 GB 4× · 49 GB free | 43 GB 2× · 21 GB free | 25 GB 1× · 6.8 GB free |
| Gemma 4 31B Google | 31.3B | 75 GB 4× · 53 GB free or 2× · 2% spare | 41 GB 2× · 23 GB free | 24 GB 1× · 8 GB free |
| GLM-4.7 Flash Z.ai | 31.2B | 75 GB 4× · 53 GB free or 2× · 2% spare | 41 GB 2× · 23 GB free | 24 GB 1× · 8 GB free |
| Qwen3.6 27B Alibaba | 27.8B | 67 GB 4× · 61 GB free or 2× · 15% spare | 37 GB 2× · 27 GB free or 1× · 4% spare | 21 GB 1× · 11 GB free |
| Mistral Small 3.2 24B Mistral AI | 24B | 58 GB 2× · 6.4 GB free | 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 |
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 · Start from a model instead
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