NVIDIA RTX 5880 Ada Generation
The NVIDIA RTX 5880 Ada Generation is an enterprise-class GPU built on the Ada Lovelace architecture, featuring 48 GB of memory with 960 GB/s of memory bandwidth and a 285 W TDP. Currently available from 1 provider starting at $0.80/GPU/hour, with a market median of $0.80/GPU/hour across 2 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 5880 Ada Generation
Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 48 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 2× · 5.7 GB free |
| gpt-oss-120b OpenAI | 117B 5.1B active | — Not released | — Not released | 78 GB 2× · 18 GB free |
| Qwen3.6 35B-A3B Alibaba | 35B 3B active | 86 GB 2× · 9.7 GB free | 47 GB Barely fits on 1× | 28 GB 1× · 20 GB free |
| Qwen3 32B Alibaba | 32.8B | 79 GB 2× · 17 GB free | 43 GB 1× · 4.8 GB free | 25 GB 1× · 23 GB free |
| Gemma 4 31B Google | 31.3B | 75 GB 2× · 21 GB free | 41 GB 1× · 6.7 GB free | 24 GB 1× · 24 GB free |
| GLM-4.7 Flash Z.ai | 31.2B | 75 GB 2× · 21 GB free | 41 GB 1× · 6.8 GB free | 24 GB 1× · 24 GB free |
| Qwen3.6 27B Alibaba | 27.8B | 67 GB 2× · 29 GB free | 37 GB 1× · 11 GB free | 21 GB 1× · 27 GB free |
| Mistral Small 3.2 24B Mistral AI | 24B | 58 GB 2× · 38 GB free | 32 GB 1× · 16 GB free | 18 GB 1× · 30 GB free |
| gpt-oss-20b OpenAI | 21B 3.6B active | — Not released | — Not released | 17 GB 1× · 31 GB free |
| Gemma 3 12B Google | 12.2B | 29 GB 1× · 19 GB free | 16 GB 1× · 32 GB free | 9.4 GB 1× · 39 GB free |
| Granite 4.1 8B IBM | 8.8B | 21 GB 1× · 27 GB free | 12 GB 1× · 36 GB free | 6.8 GB 1× · 41 GB free |
| Qwen3 8B Alibaba | 8.2B | 20 GB 1× · 28 GB free | 11 GB 1× · 37 GB free | 6.3 GB 1× · 42 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