Rent a GPU

Can the NVIDIA RTX 4090 run DeepSeek R1 Distill Qwen 7B?

RTX 4090 × DeepSeek R1 Distill Qwen 7B8K context
YesRuns fully on the GPU
Memory at FP1616.3 GB of 24 GB
Weights 15.2 GBKV cache 0.5 GBRuntime 0.6 GB
QuantFP16Full quality
Speed~40tokens per second
Max context128Kthe model's full window
  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 4090 can run DeepSeek R1 Distill Qwen 7B fully in VRAM at FP16 (full quality), using about 16.3 GB of the 24 GB available, at roughly 40 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts DeepSeek R1 Distill Qwen 7B:

ollama run deepseek-r1:7b

Ollama's default download is Q4_K_M (about 5.7 GB here). You have room for FP16, which is full quality: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the RTX 4090

Run it in the cloud

No NVIDIA RTX 4090? Run DeepSeek R1 Distill Qwen 7B 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 4090 can use.

QuantQualityMemoryFits?Speed
FP16Full quality16.3 GBFits~40 tok/s
Q8_0Near-lossless9.2 GBFits~75 tok/s
Q6_KExcellent7.3 GBFits~97 tok/s
Q5_K_MVery good6.5 GBFits~112 tok/s
Q4_K_MGood, most popular5.7 GBFits~131 tok/s
Q3_K_MNoticeably degraded4.8 GBFits~162 tok/s
Q2_KHeavily degraded3.9 GBFits~212 tok/s

Measured speed from real RTX 4090 owners

Tokens per second that people measured on their own NVIDIA RTX 4090, next to our estimate.

No one has measured DeepSeek R1 Distill Qwen 7B on the NVIDIA RTX 4090 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 4090? Add your real speed

One command times DeepSeek R1 Distill Qwen 7B 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-r1:7b

Windows (PowerShell)

$env:GPUFIT_MODEL="deepseek-r1:7b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run DeepSeek R1 Distill Qwen 7B comfortably

Models that run well on the NVIDIA RTX 4090

Frequently asked questions

Can NVIDIA RTX 4090 run DeepSeek R1 Distill Qwen 7B?

Yes. The NVIDIA RTX 4090 can run DeepSeek R1 Distill Qwen 7B fully in VRAM at FP16 (full quality), using about 16.3 GB of the 24 GB available, at roughly 40 tokens/second.

How much VRAM does DeepSeek R1 Distill Qwen 7B need?

About 5.7 GB at Q4_K_M with 8,192 tokens of context, and about 16.3 GB at full FP16 precision.

How fast is DeepSeek R1 Distill Qwen 7B on the NVIDIA RTX 4090?

Roughly 40 tokens per second at FP16, estimated from the NVIDIA RTX 4090's 1008 GB/s memory bandwidth.