Compatibility check
Can you run DeepSeek R1 Distill Qwen 32B on the RTX 2080 Ti?
Not on a single RTX 2080 Ti. Even at 4-bit, DeepSeek R1 Distill Qwen 32B needs about 19.8 GB, which exceeds the card's 11 GB. You would need roughly 2× RTX 2080 Ti with tensor parallelism, a larger GPU, or a smaller model.
Memory breakdown
Weights plus a 1 GB KV cache at 4,096tokens, against the card's 11 GB. Verdicts leave ~10% headroom for activations and fragmentation.
| Precision | Weights | KV cache | Total | % of 11 GB | Fit |
|---|---|---|---|---|---|
| FP16 / BF16full quality | 75.3 GB | 1 GB | 76.3 GB | 694% | No |
| INT8 (8-bit)near-full quality | 37.7 GB | 1 GB | 38.7 GB | 352% | No |
| INT4 (4-bit)GPTQ / AWQ / GGUF Q4 | 18.8 GB | 1 GB | 19.8 GB | 180% | No |
Planning estimates, not a substitute for profiling. Real usage varies with the inference runtime, batch size, and how much context you actually use — the KV cache grows linearly with prompt length.
GPUs that run DeepSeek R1 Distill Qwen 32B
Cards where this model fits (at its best precision):
Models that fit the RTX 2080 Ti
Other popular models that run on this card:
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Frequently asked questions
Can the RTX 2080 Ti run DeepSeek R1 Distill Qwen 32B?
No. Even 4-bit needs about 19.8 GB, more than the 11 GB available.
How much VRAM does DeepSeek R1 Distill Qwen 32B need?
Approximately 75.3 GB in FP16, 37.7 GB in INT8, and 18.8 GB in 4-bit for the weights, plus a KV cache of about 1 GB at 4,096 tokens.
Does quantization let DeepSeek R1 Distill Qwen 32B fit on the RTX 2080 Ti?
Not on a single RTX 2080 Ti — even 4-bit exceeds 11 GB. You would need multiple GPUs or a larger card.
What happens to memory with longer context?
The KV cache grows linearly with prompt length. At 4,096 tokens it is about 1 GB here; doubling the context roughly doubles that term, so long-context use can push a tight fit over the edge.