Sirva modelos de lenguaje grandes con rendimiento máximo usando vLLM en hardware NVIDIA GPU dedicado. API compatible con OpenAI fuera de la caja.
$ pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0 # Correr en NVIDIA Tesla P40 (24GB) Listo. _
vLLM es un motor de servicio LLM de alto rendimiento que utiliza PagedAtention para una gestión eficiente de la memoria. La ejecución de vLLM en una GPU VPS le proporciona una API LLM lista para la producción con un rendimiento óptimo.
Gestión eficiente de la memoria GPU para un mayor rendimiento.
Maneje múltiples solicitudes concurrentes con una utilización óptima de la GPU.
Reemplazo desplegable para los endpoints de OpenAI API.
LLaMA, Mistral, Gemma, Qwen, y arquitecturas de más de 50 modelos.
vLLM on a GPU VPS is a CUDA-accelerated deployment. vLLM is primarily an LLM-inference / chat workload. You will want fast random-access reads from disk to memory and enough VRAM for the model plus context window.
Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0. Your vLLM environment is ready in minutes with full GPU acceleration.
LLM inference VRAM scales with model parameters. A 7B model needs ~5-8 GB VRAM, 13B ~10-14 GB, 70B requires multi-GPU or quantization. Our 24 GB Tesla P40 comfortably runs 7B-13B models at full precision and 30B-class models with INT8 quantization.
GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.
Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside vLLM.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for vLLM however you need.
GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your vLLM workload.
Yes — your vLLM GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.
Keep working data on the VPS SSD for fast access during vLLM runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.
Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your vLLM install carries over.
Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long vLLM training runs where you want a checkpointable server state.
Yes — 30-day money-back guarantee on every plan including GPU. Try vLLM on a GPU VPS risk-free.
Implementar un servidor NVIDIA GPU dedicado en minutos. Sin reservas, sin llamadas de ventas.