HARDWARE FIT CHECK • DeepSeek-R1 Distill Qwen 14B + NVIDIA GeForce RTX 3060 (12GB)13.16 GB / 12 GB VRAM
Can I Run DeepSeek-R1 Distill Qwen 14B on NVIDIA GeForce RTX 3060 (12GB)?
Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running DeepSeek-R1 Distill Qwen 14B (14.8B) on NVIDIA GeForce RTX 3060 (12GB) (12 GB).
⚠️ Exceeds VRAM — Requires Partial CPU/RAM Offload (Slow)13.16 GB (110%)~5 t/s
DeepSeek-R1 Distill Qwen 14B on NVIDIA GeForce RTX 3060 (12GB)
⚠️ Partial Offload — Slow CPU/RAM Spillover
⚡ PARTIAL OFFLOAD
Required VRAM
13.16 GB
110% of hardware capacity (12 GB)Est. Decode Speed
~5 tok/s
Dense model @ 360 GB/sAvailable Headroom
-1.16 GB
Needs +1.16 GB more VRAMMemory Allocation & Headroom
13.16 GB allocated of 12 GB capacity
110% utilized
Weights: 8.88 GB
KV: (32K): 3.22 GB
Overhead: 1.06 GB
Deficit: -1.16 GB
⚡ Architecture & Throughput Transparency: Single-user decode speed (~5 tok/s) is memory-bandwidth bound at batch size = 1 on NVIDIA GeForce RTX 3060 (12GB) (360 GB/s). Prompt prefill / TTFT (~73 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run deepseek-r1:14b⚠️ 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 14B @ 13.16 GB VRAM)
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) – $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) – $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 29.6 GB | 3.22 GB | 34.61 GB (288%) | 0 t/s | OOM |
| Q8_08.5 bpw | 15.69 GB | 3.22 GB | 20.21 GB (168%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 12.14 GB | 3.22 GB | 16.53 GB (138%) | 0 t/s | OOM |
| Q5_K_M5.68 bpw | 10.51 GB | 3.22 GB | 14.85 GB (124%) | ~5 t/s | PARTIAL |
| Q4_K_M4.8 bpw | 8.88 GB | 3.22 GB | 13.16 GB (110%) | ~5 t/s | PARTIAL |
| FP44.25 bpw | 7.84 GB | 3.22 GB | 12.08 GB (101%) | ~6 t/s | PARTIAL |
| IQ3_XS3.3 bpw | 6.07 GB | 3.22 GB | 10.25 GB (85%) | ~34 t/s | FITS |
Local Hardware Configurations & Pricing
High-bandwidth VRAM specs and current market pricesConsumer GPU12 GB VRAM
NVIDIA GeForce RTX 3060 (12GB)
Entry-level budget card for 7B–14B Q4 models
360 GB/s170W TDP
$289Amazon Prime →
Consumer GPU32 GB VRAM
NVIDIA GeForce RTX 5090 (32GB GDDR7)
Maximum tokens/sec on 27B–35B models & Blackwell FP4 quantization
1792 GB/s575W TDP
$1,999Amazon Prime →
Consumer GPU24 GB VRAM
NVIDIA GeForce RTX 4090 (24GB GDDR6X)
The 24GB CUDA enthusiast standard for 14B–32B Q4_K_M models
1008 GB/s450W TDP
$1,699Amazon Prime →
Multi-GPU Rig48 GB VRAM
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
936 GB/s700W TDP
$1,550Amazon Prime →
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