DeepSeek R1 Distill Qwen 14B — Hardware Requirements & GPU Compatibility
ChatReasoning
DeepSeek R1 Distill Qwen 14B sits in a sweet spot between the smaller 7B distill and the more demanding 32B version, offering strong reasoning performance at 14.8 billion parameters on the Qwen 2.5 architecture. It captures a meaningful share of the full R1's chain-of-thought capabilities while keeping resource requirements within the range of mainstream consumer GPUs. Quantized to 4-bit, it fits comfortably on GPUs with 12 GB of VRAM, delivering reliable step-by-step reasoning for math, logic, and analytical problems.
742.0K downloads
613 likesSpecifications
- Publisher
- DeepSeek
- Family
- Qwen
- Parameters
- 14.8B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2025-02-24
- License
- MIT
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HuggingFace
How Much VRAM Does DeepSeek R1 Distill Qwen 14B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ2_XS | 2.40 | 5.1 GB | 30.5 GB | 4.43 GB | Importance-weighted 2-bit, extra small |
| IQ2_S | 2.50 | 5.3 GB | 30.7 GB | 4.62 GB | Importance-weighted 2-bit, small |
| IQ2_M | 2.70 | 5.7 GB | 31.1 GB | 4.98 GB | Importance-weighted 2-bit, medium |
| IQ3_XS | 3.30 | 6.8 GB | 32.2 GB | 6.09 GB | Importance-weighted 3-bit, extra small |
| Q2_K | 3.40 | 7.0 GB | 32.4 GB | 6.28 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 7.2 GB | 32.5 GB | 6.46 GB | 3-bit small quantization |
| IQ3_M | 3.60 | 7.3 GB | 32.7 GB | 6.65 GB | Importance-weighted 3-bit, medium |
| Q3_K_M | 3.90 | 7.9 GB | 33.3 GB | 7.20 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 8.1 GB | 33.5 GB | 7.39 GB | 4-bit legacy quantization |
| Q3_K_L | 4.10 | 8.3 GB | 33.6 GB | 7.57 GB | 3-bit large quantization |
| IQ4_XS | 4.30 | 8.6 GB | 34.0 GB | 7.94 GB | Importance-weighted 4-bit, compact |
| Q4_1 | 4.50 | 9.0 GB | 34.4 GB | 8.31 GB | 4-bit legacy quantization with offset |
| Q4_K_S | 4.50 | 9.0 GB | 34.4 GB | 8.31 GB | 4-bit small quantization |
| IQ4_NL | 4.50 | 9.0 GB | 34.4 GB | 8.31 GB | Importance-weighted 4-bit, non-linear |
| Q4_K_M | 4.80 | 9.6 GB | 34.9 GB | 8.86 GB | 4-bit medium quantization — most popular sweet spot |
| Q4_K_L | 4.90 | 9.8 GB | 35.1 GB | 9.05 GB | 4-bit large quantization |
| Q5_K_S | 5.50 | 10.9 GB | 36.2 GB | 10.15 GB | 5-bit small quantization |
| Q5_K_M | 5.70 | 11.2 GB | 36.6 GB | 10.52 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q5_K_L | 5.80 | 11.4 GB | 36.8 GB | 10.71 GB | 5-bit large quantization |
| Q6_K | 6.60 | 12.9 GB | 38.3 GB | 12.19 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 15.5 GB | 40.8 GB | 14.77 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run DeepSeek R1 Distill Qwen 14B?
Q4_K_M · 9.6 GBDeepSeek R1 Distill Qwen 14B (Q4_K_M) requires 9.6 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 34.9 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?
Q4_K_M · 9.6 GB27 devices with unified memory can run DeepSeek R1 Distill Qwen 14B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (6)
Frequently Asked Questions
- How much VRAM does DeepSeek R1 Distill Qwen 14B need?
DeepSeek R1 Distill Qwen 14B requires 9.6 GB of VRAM at Q4_K_M, or 15.5 GB at Q8_0. Full 131K context adds up to 25.4 GB (34.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 14.8B × 4.8 bits ÷ 8 = 8.9 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 26 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M9.6 GBQ4_K_M + full context34.9 GB- What's the best quantization for DeepSeek R1 Distill Qwen 14B?
For DeepSeek R1 Distill Qwen 14B, Q4_K_M (9.6 GB) offers the best balance of quality and VRAM usage. Q4_K_L (9.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XS at 5.1 GB.
VRAM requirement by quantization
IQ2_XS5.1 GB~57%Q3_K_S7.2 GB~77%IQ4_XS8.6 GB~87%Q4_K_M ★9.6 GB~89%Q4_K_L9.8 GB~90%Q8_015.5 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek R1 Distill Qwen 14B on a Mac?
DeepSeek R1 Distill Qwen 14B requires at least 5.1 GB at IQ2_XS, 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 locally?
Yes — DeepSeek R1 Distill Qwen 14B can run locally on consumer hardware. At Q4_K_M quantization it needs 9.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek R1 Distill Qwen 14B?
At Q4_K_M, DeepSeek R1 Distill Qwen 14B can reach ~305 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~69 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 ÷ 9.6 × 0.55 = ~305 tok/s
Estimated speed at Q4_K_M (9.6 GB)
AMD Instinct MI300X~305 tok/sNVIDIA GeForce RTX 4090~69 tok/sNVIDIA H100 SXM~228 tok/sAMD Instinct MI250X~189 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?
At Q4_K_M, the download is about 8.86 GB. The full-precision Q8_0 version is 14.77 GB. The smallest option (IQ2_XS) is 4.43 GB.