Can I Run DeepSeek-R1 Distill Qwen 32B on NVIDIA GeForce RTX 5070 (12GB GDDR7)?
Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running DeepSeek-R1 Distill Qwen 32B (32.8B) on NVIDIA GeForce RTX 5070 (12GB GDDR7) (12 GB).
✕ Out of Memory — Exceeds VRAM Capacity
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run deepseek-r1:32bLocal Hardware Configurations & Pricing
⚠️ Out of VRAM: High-Capacity Hardware UpgradesNVIDIA GeForce RTX 5090 (32GB GDDR7)
Maximum tokens/sec on 27B–35B models & Blackwell FP4 quantization
NVIDIA GeForce RTX 4090 (24GB GDDR6X)
The 24GB CUDA enthusiast standard for 14B–32B Q4_K_M models
2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM)
Best price-to-VRAM homelab rig for 70B Q4_K_M & Qwen 3.8 27B Q8
NVIDIA GeForce RTX 5070 (12GB GDDR7)
High-efficiency 12GB entry point with FP4 tensor acceleration
⚠️ Out of VRAM? Don't downgrade model quality.
Out of VRAMSpin up an on-demand cloud GPU instance in 60 seconds with pre-installed Ollama and vLLM. (DeepSeek-R1 Distill Qwen 32B @ 25.41 GB VRAM)
Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 65.6 GB | 4.29 GB | 72.94 GB (608%) | 0 t/s | OOM |
| Q8_08.5 bpw | 34.77 GB | 4.29 GB | 41.03 GB (342%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 26.9 GB | 4.29 GB | 32.88 GB (274%) | 0 t/s | OOM |
| Q5_K_M5.68 bpw | 23.29 GB | 4.29 GB | 29.15 GB (243%) | 0 t/s | OOM |
| Q4_K_M4.8 bpw | 19.68 GB | 4.29 GB | 25.41 GB (212%) | 0 t/s | OOM |
| FP44.25 bpw | 17.38 GB | 4.29 GB | 23.03 GB (192%) | 0 t/s | OOM |
| IQ3_XS3.3 bpw | 13.45 GB | 4.29 GB | 18.96 GB (158%) | 0 t/s | OOM |
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Frequently Asked Questions: DeepSeek-R1 Distill Qwen 32B on NVIDIA GeForce RTX 5070 (12GB GDDR7)
How much VRAM does DeepSeek-R1 Distill Qwen 32B need on NVIDIA GeForce RTX 5070 (12GB GDDR7)?
At standard 4-bit quantization (Q4_K_M) with 32K context, DeepSeek-R1 Distill Qwen 32B requires 25.41 GB of total VRAM (weights + KV cache + CUDA runtime overhead).
What inference speed will DeepSeek-R1 Distill Qwen 32B achieve on NVIDIA GeForce RTX 5070 (12GB GDDR7)?
Based on NVIDIA GeForce RTX 5070 (12GB GDDR7)'s 672 GB/s memory bandwidth, expected decode speed is approximately 0 tokens per second.
Can I expand context beyond 32K tokens?
Each additional 32K tokens of context requires additional KV cache memory. For longer context windows, consider 8-bit or 4-bit KV cache quantization.