Can RTX 4070 SUPER run DeepSeek R1 Distill 8B?
Yes — runs locally
~62 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4070 SUPER (12 GB VRAM) handles DeepSeek R1 Distill 8B comfortably using the Q5_K_M quantization, which fits in 5.8 GB. Expected throughput is around 62 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Compact reasoning model. Good reasoning capabilities in a small package.
Setup tutorial: DeepSeek R1 Distill 8B on RTX 4070 SUPER
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run DeepSeek R1 Distill 8B on an NVIDIA GeForce RTX 4070 SUPER with Q5_K_M quantization for Grade S performance at ~84 tok/sec.
Prerequisites
Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 525.60 or later, and CUDA 11.8 or later installed.
Expected performance
With the Q5_K_M quantization, you can expect ~84 tok/sec performance and 5.8GB of VRAM in use, leaving 6.2GB of VRAM for context. This allows for a practical context window of around 65536 tokens, which is sufficient for most tasks requiring long-term memory.
1. Install runtimeOllama
curl -L https://ollama.ai/install.sh | bash
ollama setup2. Download the model
Download the Q5_K_M quantized version of DeepSeek R1 Distill 8B (5.3GB file).
ollama pull bartowski/DeepSeek-R1-Distill-Llama-8B-GGUF:Q5_K_M3. Run it
ollama run DeepSeek-R1-Distill-Llama-8B-Q5_K_M
ollama chat DeepSeek-R1-Distill-Llama-8B-Q5_K_M4. Optimize for RTX 4070 SUPER
For optimal performance on the NVIDIA GeForce RTX 4070 SUPER with 12GB VRAM, set --n-gpu-layers to 40 to maximize GPU utilization while keeping VRAM usage under control. Enable flash-attn to reduce memory bandwidth usage and improve inference speed. Given the 5.8GB VRAM requirement, you will have approximately 6.2GB of VRAM left for context, allowing for a practical context window of around 65536 tokens.
Troubleshooting
Out of memory error during inference
Reduce --n-gpu-layers to 30 or lower to decrease VRAM usage.
Slow token generation speed
Ensure flash-attn is enabled and update your NVIDIA drivers to the latest version.
Model fails to load
Check if the model file is corrupted and re-download it using the 'ollama pull' command.
Alternative runtimes
For users preferring different runtimes, consider LM Studio for a more user-friendly interface, llama.cpp for fine-grained control over quantization and performance settings, or Jan for a lightweight, easy-to-deploy solution. Each runtime has its strengths, but Ollama provides a balanced approach with good performance and ease of use on the NVIDIA GeForce RTX 4070 SUPER.
Other models that run great on RTX 4070 SUPER
FAQ (20)
What GPU do I need to run DeepSeek R1 Distill 8B?
To run DeepSeek R1 Distill 8B, you need a GPU with at least 5.1 GB of VRAM for the lowest quantization level, up to 8.4 GB for the highest. NVIDIA GPUs like the RTX 3060 or higher are recommended.
Is DeepSeek R1 Distill 8B good for coding?
DeepSeek R1 Distill 8B is well-suited for coding tasks due to its strong reasoning capabilities and compact size, making it efficient for code generation and debugging.
DeepSeek R1 Distill 8B vs Llama 3.1 8B?
DeepSeek R1 Distill 8B offers better reasoning capabilities in a smaller package compared to Llama 3.1 8B, which may have a larger context length but is generally less efficient in terms of resource usage.
Can I run DeepSeek R1 Distill 8B on a Mac?
Yes, you can run DeepSeek R1 Distill 8B on a Mac with an M1 or M2 chip, but performance will be better on a Mac with a dedicated GPU like the RTX 3060 or higher.
How much VRAM does DeepSeek R1 Distill 8B need?
DeepSeek R1 Distill 8B requires between 5.1 GB and 8.4 GB of VRAM, depending on the quantization level used.
Is DeepSeek R1 Distill 8B censored?
DeepSeek R1 Distill 8B is not inherently censored, but it adheres to ethical guidelines and may filter out inappropriate content based on the training data and configuration settings.
Is DeepSeek R1 Distill 8B commercial-use allowed?
Yes, DeepSeek R1 Distill 8B is licensed under the MIT License, which allows for commercial use without restrictions.
DeepSeek R1 Distill 8B context length?
DeepSeek R1 Distill 8B has a context length of 131,072 tokens, allowing it to handle very long sequences of text.
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