作者： Jakub Rusinowski · 最后更新： 2026年7月12日
These figures are for DeepSeek-R1-Distill-Llama-8B, a distill of Llama-3.1-8B — 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, comfortably — you'll have ~3.2 GB of headroom running DeepSeek R1 Distill Llama 8B at Q4_K_M (4.83 GB, ~47 tok/s (est.)) with room for up to 16K context.
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| VRAM | 8 GB |
| Memory Bandwidth | 448 GB/s |
| Quant | VRAM needed | Fits 8 GB? | Max context |
|---|---|---|---|
| F16 | 17.3 GB | ✗ No | — |
| Q8_0 | 9.8 GB | ✗ No | — |
| Q6_K | 7.9 GB | ✓ Yes | 4K |
| Q5_K_M | 7 GB | ✓ Yes | 8K |
| Q4_K_M | 6.2 GB | ✓ Yes | 16K |
| Q3_K_M | 4.7 GB | ✓ Yes | 16K |
| Q2_K | 4 GB | ✓ Yes | 32K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 8 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| DeepSeek R1 Distill Llama 8B | Q4_K_M · 4.83 GB · ~47 tok/s (est.) |
At 2 hrs/day, buying (~$499) beats renting at $0.34/hr after about 2.0 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
Yes, comfortably — you'll have ~3.2 GB of headroom running DeepSeek R1 Distill Llama 8B at Q4_K_M (4.83 GB, ~47 tok/s (est.)) with room for up to 16K context.
DeepSeek R1 Distill Llama 8B at Q4_K_M quantization (4.83 GB), estimated ~47 tokens/sec, up to 16K context.
| Size | VRAM | Verdict | Speed |
|---|---|---|---|
| DeepSeek R1 (671B) | 405.1 GB | Does not fit | — |
| DeepSeek R1 Distill Qwen 32B | 19.3 GB | Does not fit | — |
| DeepSeek R1 Distill Qwen 14B | 8.5 GB | Runs at Q2_K | — |
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