DeepSeek R1 Distill Qwen 14B Bnb 4bit — Hardware Requirements & GPU Compatibility
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8.4K downloads
5 likesSpecifications
- Publisher
- Unsloth
- Family
- Qwen
- Parameters
- 15.2B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2025-02-14
- License
- Apache 2.0
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How Much VRAM Does DeepSeek R1 Distill Qwen 14B Bnb 4bit Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.80 | 9.8 GB | 35.2 GB | 9.11 GB | 4-bit medium quantization — most popular sweet spot |
Which GPUs Can Run DeepSeek R1 Distill Qwen 14B Bnb 4bit?
Q4_K_M · 9.8 GBDeepSeek R1 Distill Qwen 14B Bnb 4bit (Q4_K_M) requires 9.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 13+ GB is recommended. Using the full 131K context window can add up to 25.4 GB, bringing total usage to 35.2 GB. 28 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run DeepSeek R1 Distill Qwen 14B Bnb 4bit?
Q4_K_M · 9.8 GB27 devices with unified memory can run DeepSeek R1 Distill Qwen 14B Bnb 4bit, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does DeepSeek R1 Distill Qwen 14B Bnb 4bit need?
DeepSeek R1 Distill Qwen 14B Bnb 4bit requires 9.8 GB of VRAM at Q4_K_M. Full 131K context adds up to 25.4 GB (35.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 15.2B × 4.8 bits ÷ 8 = 9.1 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 26.1 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M9.8 GBQ4_K_M + full context35.2 GB- Can I run DeepSeek R1 Distill Qwen 14B Bnb 4bit on a Mac?
DeepSeek R1 Distill Qwen 14B Bnb 4bit requires at least 9.8 GB at Q4_K_M, 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 Qwen 14B Bnb 4bit locally?
Yes — DeepSeek R1 Distill Qwen 14B Bnb 4bit can run locally on consumer hardware. At Q4_K_M quantization it needs 9.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek R1 Distill Qwen 14B Bnb 4bit?
At Q4_K_M, DeepSeek R1 Distill Qwen 14B Bnb 4bit can reach ~297 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~67 tok/s. 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 ÷ 9.8 × 0.55 = ~297 tok/s
Estimated speed at Q4_K_M (9.8 GB)
AMD Instinct MI300X~297 tok/sNVIDIA GeForce RTX 4090~67 tok/sNVIDIA H100 SXM~222 tok/sAMD Instinct MI250X~184 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 Qwen 14B Bnb 4bit?
At Q4_K_M, the download is about 9.11 GB.
- Which GPUs can run DeepSeek R1 Distill Qwen 14B Bnb 4bit?
28 consumer GPUs can run DeepSeek R1 Distill Qwen 14B Bnb 4bit at Q4_K_M (9.8 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run DeepSeek R1 Distill Qwen 14B Bnb 4bit?
27 devices with unified memory can run DeepSeek R1 Distill Qwen 14B Bnb 4bit at Q4_K_M (9.8 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.