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HomeCan I run it?R1 Distill 32BR1 Distill 32B on an RTX 5080

No. R1 Distill 32B at Q4_K_M needs about 23.8 GB, and the GeForce RTX 5080 has 16.0 GB usable at a ~4k context.

Can I run R1 Distill 32B on an RTX 5080?

R1 Distill 32B at Q4_K_M needs about 23.8 GB, and the GeForce RTX 5080 has 16.0 GB usable. That figure is 16 GB of VRAM on the spec sheet, of which 16.0 GB is usable for weights and cache, at 960 GB/s memory bandwidth. A 32B DeepSeek-R1 distill on Qwen. Memory need matches Qwen3-32B; the weights are distilled from DeepSeek-R1. These are estimates from our formula, not measured benchmarks.

Quant that fits
None of Q4, Q8 or FP16 needs 23.8 GB
Memory needed
23.8 GB at Q4_K_M, ~4k context
Usable VRAM
16.0 GB of 16 GB VRAM
Est. tokens/sec
n/a does not fit

DeepSeek-R1-Distill-Qwen-32B · GeForce RTX 5080 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 16.0 GBVerdict
Q4_K_M23.8 GBQ4Won’t fit
Q8_041.0 GBQ8Won’t fit
FP1676.4 GBFP16Won’t fit

Estimated tokens per second

No speed estimate: R1 Distill 32B does not fit in the 16.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.

Context headroom

Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.

Context headroom for R1 Distill 32B on an RTX 5080 at Q4_K_M
ContextKV cache (FP16)Total at Q4_K_MVerdict
4k1.1 GB23.8 GBWon’t fit
8k2.1 GB24.9 GBWon’t fit
16k4.3 GB27.1 GBWon’t fit
32k8.6 GB31.4 GBWon’t fit
64k17.2 GB39.9 GBWon’t fit
128k34.4 GB57.1 GBWon’t fit

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

Other hardware for R1 Distill 32B

Other models on an RTX 5080

Quick answers

Can I run R1 Distill 32B on an RTX 5080?
No. R1 Distill 32B at Q4_K_M needs about 23.8 GB, and the GeForce RTX 5080 has 16.0 GB usable.
How much VRAM does R1 Distill 32B need?
About 23.8 GB at Q4_K_M, 41.0 GB at Q8_0 and 76.4 GB at FP16, estimated for a ~4k context.
How fast is R1 Distill 32B on an RTX 5080?
We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
What context length can I use?
The weights already do not fit, so longer context is not the limiting factor.

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