MODEL ARCHITECTURE SPEC โข DEEPSEEK14.8B Dense
DeepSeek-R1 Distill Qwen 14B VRAM & inference speed
14.8B Total ParamsDense Architecture48 Layers โข 8 KV Heads16K Default Ctx (Max 128K)Ollama: deepseek-r1:14b
Accurate memory requirements, KV cache footprint, and tokens/sec generation benchmarks for running DeepSeek-R1 Distill Qwen 14B across local GPUs, Apple Silicon Macs, and cloud instances.
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Runs 100% in GPU VRAM (Optimal Headroom)13.16 GB (82%)~46 t/s
DeepSeek-R1 Distill Qwen 14B on NVIDIA RTX 4070 Ti Super (16GB)
โ Fits Comfortably in VRAM
โ FITS IN VRAM
Required VRAM
13.16 GB
82% of hardware capacity (16 GB)Est. Decode Speed
~46 tok/s
Dense model @ 672 GB/sAvailable Headroom
+2.84 GB
Safe for OS display & full contextMemory Allocation & Headroom
13.16 GB allocated of 16 GB capacity
82% utilized
Weights: 8.88 GB
KV: (32K): 3.22 GB
Overhead: 1.06 GB
Free Headroom: +2.84 GB
โก Architecture & Throughput Transparency: Single-user decode speed (~46 tok/s) is memory-bandwidth bound at batch size = 1 on NVIDIA RTX 4070 Ti Super (16GB) (672 GB/s). Prompt prefill / TTFT (~667 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-r1:14bCloud Instance Options for DeepSeek-R1 Distill Qwen 14B
On-DemandDeploy this model on an on-demand cloud GPU without local hardware constraints or power usage:
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) โ $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) โ $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx โข KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 29.6 GB | 3.22 GB | 34.61 GB (216%) | 0 t/s | OOM |
| Q8_08.5 bpw | 15.69 GB | 3.22 GB | 20.21 GB (126%) | ~6 t/s | PARTIAL |
| Q6_K6.56 bpw | 12.14 GB | 3.22 GB | 16.53 GB (103%) | ~8 t/s | PARTIAL |
| Q5_K_M5.68 bpw | 10.51 GB | 3.22 GB | 14.85 GB (93%) | ~40 t/s | FITS |
| Q4_K_M4.8 bpw | 8.88 GB | 3.22 GB | 13.16 GB (82%) | ~46 t/s | FITS |
| FP44.25 bpw | 7.84 GB | 3.22 GB | 12.08 GB (76%) | ~52 t/s | FITS |
| IQ3_XS3.3 bpw | 6.07 GB | 3.22 GB | 10.25 GB (64%) | ~65 t/s | FITS |
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Hardware Compatibility Matrix for DeepSeek-R1 Distill Qwen 14B
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Hardware System | VRAM Envelope | Required VRAM | Headroom | Est. Decode Speed | Compatibility | Test Fit |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 (32GB GDDR7) Consumer GPU โข 1792 GB/s | 32 GB | 13.16 GB | +18.84 GB | ~126 tok/s | โ FITS | Test Fit โ |
| NVIDIA GeForce RTX 4090 (24GB GDDR6X) Consumer GPU โข 1008 GB/s | 24 GB | 13.16 GB | +10.84 GB | ~71 tok/s | โ FITS | Test Fit โ |
| 2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM) Multi-GPU Rig โข 936 GB/s | 48 GB | 13.16 GB | +34.84 GB | ~60 tok/s | โ FITS | Test Fit โ |
| NVIDIA GeForce RTX 5080 (16GB GDDR7) Consumer GPU โข 960 GB/s | 16 GB | 13.16 GB | +2.84 GB | ~67 tok/s | โ FITS | Test Fit โ |
| NVIDIA RTX 4070 Ti Super (16GB) Consumer GPU โข 672 GB/s | 16 GB | 13.16 GB | +2.84 GB | ~46 tok/s | โ FITS | Test Fit โ |
| NVIDIA GeForce RTX 3060 (12GB) Consumer GPU โข 360 GB/s | 12 GB | 13.16 GB | -1.16 GB | ~5 tok/s | โก PARTIAL | Test Fit โ |
| Apple Mac Mini M4 Pro (64GB Unified Memory) Apple Silicon โข 273 GB/s | 54 GB | 13.16 GB | +40.84 GB | ~18 tok/s | โ FITS | Test Fit โ |
| Apple Mac Studio M4 Max (128GB Unified Memory) Apple Silicon โข 546 GB/s | 112 GB | 13.16 GB | +98.84 GB | ~36 tok/s | โ FITS | Test Fit โ |
| Apple Mac Studio M5 Ultra (256GB Unified Memory) Apple Silicon โข 890 GB/s | 236 GB | 13.16 GB | +222.84 GB | ~59 tok/s | โ FITS | Test Fit โ |
| AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) Unified APU / Mini-PC โข 256 GB/s | 110 GB | 13.16 GB | +96.84 GB | ~15 tok/s | โ FITS | Test Fit โ |
| NVIDIA DGX Spark (128GB Grace-Blackwell Unified) AI Appliance โข 273 GB/s | 118 GB | 13.16 GB | +104.84 GB | ~19 tok/s | โ FITS | Test Fit โ |
| NVIDIA H100 SXM (80GB HBM3 Cloud GPU) Datacenter Cloud GPU โข 3350 GB/s | 80 GB | 13.16 GB | +66.84 GB | ~249 tok/s | โ FITS | Test Fit โ |