✅ EJECUTA FP16 NATIVO Y TODAS LAS CUANTIZACIONES

Qwen3-14B on 8x NVIDIA H100 80GB (640GB) (640GB VRAM)

In 4-bit GGUF Q4_K_M, Qwen3-14B consumes 10.36 GB (8.62 GB weights + 1.25 GB KV cache at 8K context), achieving ~258.2 tokens/sec decode and ~18000 tokens/sec prefill.

🎛️ Ajustador Interactivo de VRAM, Contexto y Offload

📊 Telemetría de Memoria y Rendimiento en Tiempo Real

10.36 GB / 640 GB
🟦 Pesos del Modelo: 8.62 GB 🟪 Caché KV: 1.25 GB 🟨 Buffer del Motor: 0.49 GB
VRAM de GPU Requerida10.36 GB
RAM de Sistema Requerida (CPU)0.00 GB
VRAM Disponible en Hardware640 GB (1x 8x NVIDIA H100 80GB (640GB))
Margen / Déficit de VRAM629.64 GB
Velocidad de Generación (Decode)~258.2 tokens/sec
Velocidad de Procesamiento (Prefill)~18000 tokens/sec
Tiempo al Primer Token (Prompt 4K)~228 ms
Topología TransformerDense-GQA (40L, 8/40 KV/Q heads)

🚀 Comando de Lanzamiento Listo para Copiar

ollama run qwen3:14b
# Or llama.cpp server (8K context, Flash Attention):
llama-server -hf Qwen/Qwen3-14B-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 (Qwen3-14B: 10.36 GB in 4-bit)

Recommended Cloud Tier: RTX 4090 (24GB) · Full FP16 Needs: 29.7 GB

Meses para amortizar compra vs alquiler: ~32 months (vs $230,000 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: Qwen3-14B × 8x NVIDIA H100 80GB (640GB)

Quantization Format Core / Emb BPW Weights (GiB) KV Cache (8K) Total VRAM 1x 8x NVIDIA H100 80GB (640GB) (640GB) Decode / Prefill Min GPUs
FP16 / BF16 (Unquantized) 16 / 16 27.51 GB 1.25 GB 29.25 GB Sí (5%) ~77.9 / 18000 tok/s 1x
FP8 (W8A8 / E4M3) 8.25 / 8.5 14.23 GB 1.25 GB 15.97 GB Sí (2%) ~151.1 / 18000 tok/s 1x
GGUF Q8_0 (8.50 bpw) 8.5 / 8.5 14.62 GB 1.25 GB 16.36 GB Sí (3%) ~146.7 / 18000 tok/s 1x
GGUF Q6_K (6.56 bpw) 6.56 / 6.56 11.28 GB 1.25 GB 13.02 GB Sí (2%) ~190.1 / 18000 tok/s 1x
GGUF Q5_K_M (5.69 bpw) 5.69 / 6.56 9.94 GB 1.25 GB 11.68 GB Sí (2%) ~219.1 / 18000 tok/s 1x
GGUF Q4_K_M / AWQ (4.83 bpw) 4.83 / 6.56 8.62 GB 1.25 GB 10.36 GB Sí (2%) ~258.2 / 18000 tok/s 1x
GGUF IQ4_XS (4.25 bpw) 4.25 / 5.5 7.53 GB 1.25 GB 9.28 GB Sí (1%) ~293.4 / 18000 tok/s 1x
GGUF Q3_K_M (3.91 bpw) 3.91 / 5 6.92 GB 1.25 GB 8.66 GB Sí (1%) ~318.9 / 18000 tok/s 1x

Probar este Modelo en Otras GPUs

Qwen3-14B on NVIDIA RTX 5090 (32GB)Qwen3-14B on NVIDIA RTX 4090 (24GB)Qwen3-14B on NVIDIA RTX 5080 (16GB)Qwen3-14B on NVIDIA RTX 4080 Super (16GB)Qwen3-14B on NVIDIA RTX 4070 Ti Super (16GB)Qwen3-14B on NVIDIA RTX 3090 (24GB)Qwen3-14B on NVIDIA RTX 4060 Ti 16GB (16GB)Qwen3-14B on NVIDIA RTX 3060 12GB (12GB)Qwen3-14B on NVIDIA RTX 6000 Ada (48GB)Qwen3-14B on NVIDIA RTX A6000 (48GB)

Otros Modelos en esta GPU

DeepSeek-R1 671B (MoE) on 8x NVIDIA H100 80GB (640GB)DeepSeek-V3-0324 671B (MoE) on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Llama-70B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-32B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-14B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Llama-8B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-7B on 8x NVIDIA H100 80GB (640GB)Qwen3-235B-A22B (MoE) on 8x NVIDIA H100 80GB (640GB)Qwen3-30B-A3B (MoE) on 8x NVIDIA H100 80GB (640GB)Qwen3-32B on 8x NVIDIA H100 80GB (640GB)