Rent a GPU

Can the NVIDIA RTX 3090 run DeepSeek R1 Distill Qwen 14B?

RTX 3090 × DeepSeek R1 Distill Qwen 14B8K context
YesRuns fully on the GPU
Memory at Q8_017.9 GB of 24 GB
Weights 15.7 GBKV cache 1.6 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Speed~36tokens per second
Max context37Ktokens that fit at Q8_0
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The NVIDIA RTX 3090 can run DeepSeek R1 Distill Qwen 14B fully in VRAM at Q8_0 (near-lossless), using about 17.9 GB of the 24 GB available, at roughly 36 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts DeepSeek R1 Distill Qwen 14B:

ollama run deepseek-r1:14b

Ollama's default download is Q4_K_M (about 11.2 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the RTX 3090

Run it in the cloud

No NVIDIA RTX 3090? Run DeepSeek R1 Distill Qwen 14B in the cloud.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Rent a GPU on RunPodRent a GPU on Vast.ai

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 24 GB the NVIDIA RTX 3090 can use.

QuantQualityMemoryFits?Speed
FP16Full quality31.8 GBToo big—
Q8_0Near-lossless17.9 GBFits~36 tok/s
Q6_KExcellent14.3 GBFits~46 tok/s
Q5_K_MVery good12.7 GBFits~53 tok/s
Q4_K_MGood, most popular11.2 GBFits~63 tok/s
Q3_K_MNoticeably degraded9.4 GBFits~78 tok/s
Q2_KHeavily degraded7.8 GBFits~101 tok/s

Measured speed from real RTX 3090 owners

Tokens per second that people measured on their own NVIDIA RTX 3090, next to our estimate.

No one has measured DeepSeek R1 Distill Qwen 14B on the NVIDIA RTX 3090 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 3090? Add your real speed

One command times DeepSeek R1 Distill Qwen 14B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- deepseek-r1:14b

Windows (PowerShell)

$env:GPUFIT_MODEL="deepseek-r1:14b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run DeepSeek R1 Distill Qwen 14B comfortably

Models that run well on the NVIDIA RTX 3090

Frequently asked questions

Can NVIDIA RTX 3090 run DeepSeek R1 Distill Qwen 14B?

Yes. The NVIDIA RTX 3090 can run DeepSeek R1 Distill Qwen 14B fully in VRAM at Q8_0 (near-lossless), using about 17.9 GB of the 24 GB available, at roughly 36 tokens/second.

How much VRAM does DeepSeek R1 Distill Qwen 14B need?

About 11.2 GB at Q4_K_M with 8,192 tokens of context, and about 31.8 GB at full FP16 precision.

How fast is DeepSeek R1 Distill Qwen 14B on the NVIDIA RTX 3090?

Roughly 36 tokens per second at Q8_0, estimated from the NVIDIA RTX 3090's 936 GB/s memory bandwidth.