DeepSeek R1 Distill Qwen 1.5B — Hardware Requirements & GPU Compatibility
ChatReasoning
32.8K downloads
35 likesSpecifications
- Publisher
- litert-community
- Family
- Qwen
- Parameters
- 1.5B
- Release Date
- 2025-09-22
- License
- MIT
Get Started
How Much VRAM Does DeepSeek R1 Distill Qwen 1.5B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ2_XXS | 2.20 | 0.5 GB | — | 0.41 GB | Importance-weighted 2-bit, extreme compression — significant quality loss |
| IQ2_M | 2.70 | 0.6 GB | — | 0.51 GB | Importance-weighted 2-bit, medium |
| IQ3_XXS | 3.10 | 0.6 GB | — | 0.58 GB | Importance-weighted 3-bit |
| Q2_K | 3.40 | 0.7 GB | — | 0.64 GB | 2-bit quantization with K-quant improvements |
| Q3_K_M | 3.90 | 0.8 GB | — | 0.73 GB | 3-bit medium quantization |
| IQ4_XS | 4.30 | 0.9 GB | — | 0.81 GB | Importance-weighted 4-bit, compact |
| Q4_K_M | 4.80 | 1.0 GB | — | 0.90 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 1.2 GB | — | 1.07 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 1.4 GB | — | 1.24 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 1.6 GB | — | 1.50 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run DeepSeek R1 Distill Qwen 1.5B?
Q4_K_M · 1.0 GBDeepSeek R1 Distill Qwen 1.5B (Q4_K_M) requires 1.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run DeepSeek R1 Distill Qwen 1.5B?
Q4_K_M · 1.0 GB33 devices with unified memory can run DeepSeek R1 Distill Qwen 1.5B, 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 1.5B need?
DeepSeek R1 Distill Qwen 1.5B requires 1.0 GB of VRAM at Q4_K_M, or 1.6 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 1.5B × 4.8 bits ÷ 8 = 0.9 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M1.0 GB- What's the best quantization for DeepSeek R1 Distill Qwen 1.5B?
For DeepSeek R1 Distill Qwen 1.5B, Q4_K_M (1.0 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 0.5 GB.
VRAM requirement by quantization
IQ2_XXS0.5 GB~53%IQ3_XXS0.6 GB~70%IQ4_XS0.9 GB~87%Q4_K_M ★1.0 GB~89%Q5_K_M1.2 GB~92%Q8_01.6 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek R1 Distill Qwen 1.5B on a Mac?
DeepSeek R1 Distill Qwen 1.5B requires at least 0.5 GB at IQ2_XXS, 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 1.5B locally?
Yes — DeepSeek R1 Distill Qwen 1.5B can run locally on consumer hardware. At Q4_K_M quantization it needs 1.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek R1 Distill Qwen 1.5B?
At Q4_K_M, DeepSeek R1 Distill Qwen 1.5B can reach ~2944 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~662 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 ÷ 1.0 × 0.55 = ~2944 tok/s
Estimated speed at Q4_K_M (1.0 GB)
AMD Instinct MI300X~2944 tok/sNVIDIA GeForce RTX 4090~662 tok/sNVIDIA H100 SXM~2201 tok/sAMD Instinct MI250X~1820 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 1.5B?
At Q4_K_M, the download is about 0.90 GB. The full-precision Q8_0 version is 1.50 GB. The smallest option (IQ2_XXS) is 0.41 GB.
- Which GPUs can run DeepSeek R1 Distill Qwen 1.5B?
35 consumer GPUs can run DeepSeek R1 Distill Qwen 1.5B at Q4_K_M (1.0 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run DeepSeek R1 Distill Qwen 1.5B?
33 devices with unified memory can run DeepSeek R1 Distill Qwen 1.5B at Q4_K_M (1.0 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.