Written by Jakub Rusinowski · Last updated January 20, 2025
These figures are for DeepSeek-R1-Distill-Qwen-14B, a distill of Qwen2.5-14B — not the full DeepSeek R1. The full DeepSeek R1 (671B) needs about 405 GB of weights at Q4_K_M and is a different model.
Yes, but it is tight
Yes, but it is tight — DeepSeek R1 Distill Qwen 14B at Q8_0 needs about 17 GB of the 18 GB usable on MacBook Pro 14" (M4 Pro, 24 GB), leaving only ~1 GB before the runtime starts swapping. Expect ~9.4 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~9.4 tok/s
| Usable memory for models | 18 GB |
| Memory bandwidth | 273 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
| Price | $1,999 (lib/data/laptops.ts (street price), checked 2026-07-06) |
| Quant | Memory needed | Fits 18 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 30.1 GB | ✗ No | — | — | 28 GB |
| Q8_0 | 17 GB | ✓ Yes | 8K | ~9.4 tok/s | 14.9 GB |
| Q6_K | 13.6 GB | ✓ Yes | 32K | ~11.9 tok/s | 11.5 GB |
| Q5_K_M | 12.1 GB | ✓ Yes | 32K | ~13.6 tok/s | 9.9 GB |
| Q4_K_M | 10.6 GB | ✓ Yes | 32K | ~15.6 tok/s | 8.5 GB |
| Q3_K_M | 8.1 GB | ✓ Yes | 64K | ~21.1 tok/s | 6 GB |
| Q2_K | 6.7 GB | ✓ Yes | 64K | ~26.1 tok/s | 4.6 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| DeepSeek R1 (671B) | 406.5 GB | ✗ Too large | — |
| DeepSeek R1 Distill Qwen 32B | 22.3 GB | ✗ Too large | — |
| DeepSeek R1 Distill Qwen 14B | 10.6 GB | ✓ Fits | ~15.6 tok/s |
| DeepSeek R1 Distill Llama 8B | 6.7 GB | ✓ Fits | ~25.7 tok/s |
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Yes, but it is tight — DeepSeek R1 Distill Qwen 14B at Q8_0 needs about 17 GB of the 18 GB usable on MacBook Pro 14" (M4 Pro, 24 GB), leaving only ~1 GB before the runtime starts swapping. Expect ~9.4 tok/s (estimated), with room for about 8,192 tokens of context.
Q8_0 — it needs about 17 GB of the 18 GB available, downloads as roughly 14.9 GB, and runs at an estimated 9.4 tokens/sec with up to 8K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
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