Skip to content

text model · DeepSeek-R1-Distill · Windows

Can I run DeepSeek-R1-Distill-Llama 8B on Nvidia GeForce RTX 2060 (6GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. DeepSeek-R1-Distill-Llama 8B needs ~6.4 GB even at Q4_K_M, but Nvidia GeForce RTX 2060 (6GB) only has ~5 GB usable.

Needs ~6.4 GB Device usable ~5 GB

Needs ~6.4 GB even at Q4_K_M, but only ~5 GB is usable.

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

The gap is about 1.4 GB: DeepSeek-R1-Distill-Llama 8B needs roughly 6.4 GB at Q4_K_M and Nvidia GeForce RTX 2060 (6GB) leaves only about 5 GB usable for a model. The lightest tracked hardware that runs DeepSeek-R1-Distill-Llama 8B is the Nvidia GeForce RTX 3060 Ti (8GB) at 8 GB. See DeepSeek-R1-Distill-Llama 8B on Nvidia GeForce RTX 3060 Ti (8GB).

Q4_K_M needed
~6.4 GB
Usable on device
~5 GB
Device memory
6 GB
Share on X Share on Reddit

Which quant fits

Quant ladder vs ~5 GB usable
Q2_K
~4.9 GB
Q3_K_M
~5.4 GB
Q4_K_M
~6.4 GB
Q5_K_M
~7.2 GB
Q6_K
~8.1 GB
Q8_0
~10 GB
FP16
~17.5 GB
The line marks Nvidia GeForce RTX 2060 (6GB)'s ~5 GB budget; rungs past it are too large.
Model DeepSeek-R1-Distill
Parameters
8B
Q4_K_M size
4.92 GB
Q8_0 size
8.54 GB
Context
128k
Ollama tag
deepseek-r1:8b
Full DeepSeek-R1-Distill-Llama 8B requirements →
Device Windows
Memory
6 GB vram
Usable for weights
~5 GB
Power draw
~160 W
Best runtime
Ollama (CUDA) / llama.cpp CUDA
Best models for Nvidia GeForce RTX 2060 (6GB) →

What you can run instead

Run DeepSeek-R1-Distill-Llama 8B on other hardware

FAQ

Can Nvidia GeForce RTX 2060 (6GB) run DeepSeek-R1-Distill-Llama 8B?

No. DeepSeek-R1-Distill-Llama 8B needs ~6.4 GB even at Q4_K_M, but Nvidia GeForce RTX 2060 (6GB) only has ~5 GB usable.

How much memory does DeepSeek-R1-Distill-Llama 8B need?

Nvidia GeForce RTX 2060 (6GB) does not have enough memory. At Q4_K_M the weights are ~4.92 GB; with KV cache and runtime overhead, budget ~6.4 GB at a 4k context.

What is the best tool to run DeepSeek-R1-Distill-Llama 8B 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.

Embed this

DeepSeek-R1-Distill-Llama 8B on Nvidia GeForce RTX 2060 (6GB) compatibility badge A live badge for your model card or README, updated as the data is.
Markdown
$ [![DeepSeek-R1-Distill-Llama 8B on Nvidia GeForce RTX 2060 (6GB)](https://localmodel.run/badge/deepseek-r1-distill-llama-8b/nvidia-rtx-2060-6gb.svg)](https://localmodel.run/can-i-run/deepseek-r1-distill-llama-8b/nvidia-rtx-2060-6gb)

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.