Can I Run DeepSeek-R1-Distill-Llama-8B on NVIDIA GeForce RTX 3070 Ti?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 2026
Yes, comfortably — DeepSeek R1 Distill Llama 8B at Q4_K_M needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), leaving ~1.3 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~61 tok/s (est.), with room for up to 16K context.
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.
See what else this hardware can run →
lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)
Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.
NVIDIA GeForce RTX 3070 Ti Specs
| VRAM | 8 GB |
| Memory Bandwidth | 608 GB/s |
DeepSeek R1 Distill Llama 8B on the NVIDIA GeForce RTX 3070 Ti: VRAM by quantization
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 17.9 GB | ✗ No | — | — |
| Q8_0 | 10.4 GB | ✗ No | — | — |
| Q6_K | 8.4 GB | ✗ No | — | — |
| Q5_K_M | 7.5 GB | ✓ Yes | 8K | — |
| Q4_K_M | 6.7 GB | ✓ Yes | 16K | — |
| Q3_K_M | 5.3 GB | ✓ Yes | 16K | — |
| Q2_K | 4.5 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “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.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 3070 Ti: 8K 6.7 GB · 32K 9.9 GB ✗ · 128K 22.8 GB ✗. Past 32K it no longer fits 8 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? DeepSeek R1 Distill Llama 8B on 8 GB of system RAM, CPU only: runs.
DeepSeek R1 Sizes That Fit the NVIDIA GeForce RTX 3070 Ti (at 8K context)
| DeepSeek R1 Distill Llama 8B | Q4_K_M · 6.7 GB at 8K context · ~61 tok/s (est.) |
At 2 hrs/day, buying (~$599) beats renting at $0.34/hr after about 2.4 years.
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Can I run DeepSeek R1 on the NVIDIA GeForce RTX 3070 Ti?
Yes, comfortably — DeepSeek R1 Distill Llama 8B at Q4_K_M needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), leaving ~1.3 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~61 tok/s (est.), with room for up to 16K context.
What's the best DeepSeek R1 size for the NVIDIA GeForce RTX 3070 Ti?
DeepSeek R1 Distill Llama 8B at Q4_K_M quantization needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), estimated ~61 tokens/sec, up to 16K context.
Every DeepSeek R1 size on the NVIDIA GeForce RTX 3070 Ti
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| DeepSeek R1 (671B) | 406.5 GB | Does not fit | — |
| DeepSeek R1 Distill Qwen 32B | 22.3 GB | Does not fit | — |
| DeepSeek R1 Distill Qwen 14B | 10.6 GB | Runs at Q2_K | — |
DeepSeek R1 on Other GPUs
- DeepSeek R1 on NVIDIA GeForce RTX 5060 Ti 8GB
- DeepSeek R1 on NVIDIA GeForce RTX 5060
- DeepSeek R1 on NVIDIA GeForce RTX 4060
- DeepSeek R1 on NVIDIA GeForce RTX 3070
- DeepSeek R1 on AMD Radeon RX 9060 XT 8GB
Popular Models on the NVIDIA GeForce RTX 3070 Ti
VRAM Tier
Troubleshooting
Buying Guide
← Can I Run It? | DeepSeek R1 Model Page | NVIDIA GeForce RTX 3070 Ti GPU Page | VRAM calculator | Check Your Hardware