text model · DeepSeek-R1 · Windows

Can I run DeepSeek-R1-0528 on Nvidia GeForce RTX 4060 Ti (16GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. DeepSeek-R1-0528 needs ~384.1 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.

Needs ~384.1 GB Device usable ~15 GB

Needs ~384.1 GB even at Q4_K_M, but only ~15 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 369.1 GB: DeepSeek-R1-0528 needs roughly 384.1 GB at Q4_K_M and Nvidia GeForce RTX 4060 Ti (16GB) leaves only about 15 GB usable for a model. No single tracked device has enough memory; DeepSeek-R1-0528 needs a multi-GPU or high-memory rig.

Q4_K_M needed: ~384.1 GB
Usable on device: ~15 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~15 GB usable

Q2_K

~288 GB

Q3_K_M

~335 GB

Q4_K_M

~384.1 GB

Q5_K_M

~485.1 GB

Q6_K

~557.2 GB

Q8_0

~671.3 GB

FP16

~1355 GB

The line marks Nvidia GeForce RTX 4060 Ti (16GB)'s ~15 GB budget; rungs past it are too large.

Model DeepSeek-R1

Parameters: 671B (MoE, 37B active)
Q4_K_M size: 377.13 GB
Q8_0 size: 664.3 GB
Context: 160k
Ollama tag: deepseek-r1:671b

Full DeepSeek-R1-0528 requirements →

Device Windows

Memory: 16 GB vram
Usable for weights: ~15 GB
Power draw: ~165 W
Best runtime: Ollama (CUDA) / llama.cpp CUDA

Best models for Nvidia GeForce RTX 4060 Ti (16GB) →

What you can run instead

FAQ

Can Nvidia GeForce RTX 4060 Ti (16GB) run DeepSeek-R1-0528?

No. DeepSeek-R1-0528 needs ~384.1 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.

How much memory does DeepSeek-R1-0528 need?

Nvidia GeForce RTX 4060 Ti (16GB) does not have enough memory. At Q4_K_M the weights are ~377.13 GB; with KV cache and runtime overhead, budget ~384.1 GB at a 4k context. It is a Mixture-of-Experts model (671B total / 37B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run DeepSeek-R1-0528 on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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[![DeepSeek-R1-0528 on Nvidia GeForce RTX 4060 Ti (16GB)](https://localmodel.run/badge/deepseek-r1-0528/nvidia-rtx-4060-ti-16gb.svg)](https://localmodel.run/can-i-run/deepseek-r1-0528/nvidia-rtx-4060-ti-16gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.