Can I Run DeepSeek R1 Distill Qwen 1.5B on a Apple M1 (8GB)?
Runs at full precision (fp16). Zero quality loss.
13 quantizations fit your 8.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 4.6 GB | 6.1 GB | 3.6 GB | +3.4 GB |
| Q8_0 | 2.9 GB | 4.4 GB | 1.9 GB | +5.1 GB |
| Q6_K | 2.5 GB | 4.0 GB | 1.5 GB | +5.5 GB |
| Q5_K_M | 2.3 GB | 3.8 GB | 1.3 GB | +5.7 GB |
| Q5_K_S | 2.2 GB | 3.7 GB | 1.3 GB | +5.8 GB |
| Q4_1 | 2.1 GB | 3.6 GB | 1.2 GB | +5.9 GB |
| Q4_K_M | 2.1 GB | 3.6 GB | 1.1 GB | +5.9 GB |
| Q4_K_S | 2.0 GB | 3.5 GB | 1.1 GB | +6.0 GB |
| Q4_0 | 2.0 GB | 3.5 GB | 1.1 GB | +6.0 GB |
| Q3_K_L | 1.8 GB | 3.3 GB | 1.0 GB | +6.2 GB |
| Q3_K_M | 1.8 GB | 3.3 GB | 0.9 GB | +6.3 GB |
| Q3_K_S | 1.7 GB | 3.2 GB | 0.9 GB | +6.3 GB |
| Q2_K | 1.6 GB | 3.1 GB | 0.8 GB | +6.4 GB |
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Top-ranked open-source models that fit in 8.0GB.
FAQ
Can the Apple M1 (8GB) run DeepSeek R1 Distill Qwen 1.5B?
Yes. The Apple M1 (8GB)'s 8.0GB of unified memory is enough to run DeepSeek R1 Distill Qwen 1.5B at fp16 quantization (4.6GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 8.0GB. It uses about 4.6GB of memory and 6.1GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.