✅ EJECUTA FP16 NATIVO Y TODAS LAS CUANTIZACIONES

DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 3090 (24GB VRAM)

In 4-bit GGUF Q4_K_M, DeepSeek-R1-Distill-Llama-8B consumes 6.22 GB (4.73 GB weights + 1 GB KV cache at 8K context), achieving ~132.7 tokens/sec decode and ~2299 tokens/sec prefill.

🎛️ Ajustador Interactivo de VRAM, Contexto y Offload

📊 Telemetría de Memoria y Rendimiento en Tiempo Real

6.22 GB / 24 GB
🟦 Pesos del Modelo: 4.73 GB 🟪 Caché KV: 1 GB 🟨 Buffer del Motor: 0.49 GB
VRAM de GPU Requerida6.22 GB
RAM de Sistema Requerida (CPU)0.00 GB
VRAM Disponible en Hardware24 GB (1x NVIDIA RTX 3090)
Margen / Déficit de VRAM17.78 GB
Velocidad de Generación (Decode)~132.7 tokens/sec
Velocidad de Procesamiento (Prefill)~2299 tokens/sec
Tiempo al Primer Token (Prompt 4K)~1782 ms
Topología TransformerDense-GQA (32L, 8/32 KV/Q heads)

🚀 Comando de Lanzamiento Listo para Copiar

ollama run deepseek-r1:8b
# Or llama.cpp server (8K context, Flash Attention):
llama-server -hf deepseek-ai/DeepSeek-R1-Distill-Llama-8B-GGUF -c 8192 -ngl 99 -fa
COMPARADOR CLOUD GPU Y CALCULADORA ALQUILAR VS COMPRAR

¿No tienes suficiente VRAM? Alquila una GPU en la nube en 60 segundos (DeepSeek-R1-Distill-Llama-8B: 6.22 GB in 4-bit)

Recommended Cloud Tier: RTX 4090 (24GB) · Full FP16 Needs: 16.89 GB

Meses para amortizar compra vs alquiler: ~32 months (vs $750 hardware)
Cloud Provider RTX 4090 (24GB) A100 (80GB) H100 (80GB) Est. Monthly Cost (4h/day) Free Credit / Trial Deploy
RunPod $0.44 / hr $1.39 / hr $2.39 / hr $52.80 / mo Instant PyTorch / vLLM Templates + Serverless GPU Desplegar en RunPod →
Vast.ai $0.29 / hr $0.95 / hr $1.79 / hr $34.80 / mo Save 50–70% on RTX 4090 / 5090 / A100 rentals Alquilar GPU Spot →
Vultr Cloud GPU — $1.79 / hr $2.69 / hr $214.80 / mo (A100) $300 Free Credit Reclamar $300 Gratis →
DigitalOcean GPU — — $2.99 / hr $358.80 / mo (H100) $200 Free Credit (60d) Obtener $200 Gratis →

Desglose Completo por Formato de Cuantización: DeepSeek-R1-Distill-Llama-8B × NVIDIA RTX 3090

Quantization Format Core / Emb BPW Weights (GiB) KV Cache (8K) Total VRAM 1x NVIDIA RTX 3090 (24GB) Decode / Prefill Min GPUs
FP16 / BF16 (Unquantized) 16 / 16 14.96 GB 1 GB 16.45 GB Sí (69%) ~40.1 / 2299 tok/s 1x
FP8 (W8A8 / E4M3) 8.25 / 8.5 7.74 GB 1 GB 9.23 GB Sí (38%) ~77.7 / 2299 tok/s 1x
GGUF Q8_0 (8.50 bpw) 8.5 / 8.5 7.95 GB 1 GB 9.43 GB Sí (39%) ~75.4 / 2299 tok/s 1x
GGUF Q6_K (6.56 bpw) 6.56 / 6.56 6.13 GB 1 GB 7.62 GB Sí (32%) ~97.7 / 2299 tok/s 1x
GGUF Q5_K_M (5.69 bpw) 5.69 / 6.56 5.43 GB 1 GB 6.91 GB Sí (29%) ~112.6 / 2299 tok/s 1x
GGUF Q4_K_M / AWQ (4.83 bpw) 4.83 / 6.56 4.73 GB 1 GB 6.22 GB Sí (26%) ~132.7 / 2299 tok/s 1x
GGUF IQ4_XS (4.25 bpw) 4.25 / 5.5 4.13 GB 1 GB 5.61 GB Sí (23%) ~150.8 / 2299 tok/s 1x
GGUF Q3_K_M (3.91 bpw) 3.91 / 5 3.79 GB 1 GB 5.28 GB Sí (22%) ~163.9 / 2299 tok/s 1x

Probar este Modelo en Otras GPUs

DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 5090 (32GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 4090 (24GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 5080 (16GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 4080 Super (16GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 4070 Ti Super (16GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 4060 Ti 16GB (16GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 3060 12GB (12GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX 6000 Ada (48GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA RTX A6000 (48GB)DeepSeek-R1-Distill-Llama-8B on NVIDIA L40S 48GB (48GB)

Otros Modelos en esta GPU

DeepSeek-R1 671B (MoE) on NVIDIA RTX 3090DeepSeek-V3-0324 671B (MoE) on NVIDIA RTX 3090DeepSeek-R1-Distill-Llama-70B on NVIDIA RTX 3090DeepSeek-R1-Distill-Qwen-32B on NVIDIA RTX 3090DeepSeek-R1-Distill-Qwen-14B on NVIDIA RTX 3090DeepSeek-R1-Distill-Qwen-7B on NVIDIA RTX 3090Qwen3-235B-A22B (MoE) on NVIDIA RTX 3090Qwen3-30B-A3B (MoE) on NVIDIA RTX 3090Qwen3-32B on NVIDIA RTX 3090Qwen3-14B on NVIDIA RTX 3090