DeepSeek R1 Distill Llama 70B Q3 K S GGUF — Hardware Requirements & GPU Compatibility
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13 downloadsSpecifications
- Publisher
- roleplaiapp
- Family
- Llama
- Parameters
- 70B
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How Much VRAM Does DeepSeek R1 Distill Llama 70B Q3 K S GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q3_K_S | 3.50 | 33.7 GB | — | 30.63 GB | 3-bit small quantization |
Which GPUs Can Run DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
Q3_K_S · 33.7 GBDeepSeek R1 Distill Llama 70B Q3 K S GGUF (Q3_K_S) requires 33.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 44+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
Q3_K_S · 33.7 GB13 devices with unified memory can run DeepSeek R1 Distill Llama 70B Q3 K S GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroom
Related Models
Frequently Asked Questions
- How much VRAM does DeepSeek R1 Distill Llama 70B Q3 K S GGUF need?
DeepSeek R1 Distill Llama 70B Q3 K S GGUF requires 33.7 GB of VRAM at Q3_K_S.
VRAM = Weights + KV Cache + Overhead
Weights = 70B × 3.5 bits ÷ 8 = 30.6 GB
KV Cache + Overhead ≈ 3.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q3_K_S33.7 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
No — DeepSeek R1 Distill Llama 70B Q3 K S GGUF requires at least 33.7 GB at Q3_K_S, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run DeepSeek R1 Distill Llama 70B Q3 K S GGUF on a Mac?
DeepSeek R1 Distill Llama 70B Q3 K S GGUF requires at least 33.7 GB at Q3_K_S, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run DeepSeek R1 Distill Llama 70B Q3 K S GGUF locally?
Yes — DeepSeek R1 Distill Llama 70B Q3 K S GGUF can run locally on consumer hardware. At Q3_K_S quantization it needs 33.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
At Q3_K_S, DeepSeek R1 Distill Llama 70B Q3 K S GGUF can reach ~87 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 33.7 × 0.55 = ~87 tok/s
Estimated speed at Q3_K_S (33.7 GB)
AMD Instinct MI300X~87 tok/sNVIDIA H100 SXM~65 tok/sAMD Instinct MI250X~54 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
At Q3_K_S, the download is about 30.63 GB.
- Which GPUs can run DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
No single consumer GPU has enough VRAM to run DeepSeek R1 Distill Llama 70B Q3 K S GGUF at Q3_K_S (33.7 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek R1 Distill Llama 70B Q3 K S GGUF?
13 devices with unified memory can run DeepSeek R1 Distill Llama 70B Q3 K S GGUF at Q3_K_S (33.7 GB), including Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.