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DeepSeek V4-Pro

DeepSeek V4-Pro — Especificaciones

DesarrolladorDeepSeek
TipoLLM (MoE)
ModalidadTexto → Texto
Parámetros1,6 billones en total / ~49 mil millones activos (MoE)
Ventana de contexto1 millón
Salida máxima384 K
LicenciaMIT (abierto)
Pesos abiertos
Lanzado2026-04
Precio de entrada0,435 USD / 1 millón
Precio de salida0,87 USD / 1 millón
Proveedores de APIDeepSeek, OpenRouter

Ejecútelo localmente

VRAM (4 bits)~800 GB
GPU mínimaServidor multi-GPU (p. ej., 8× H100 de 80 GB)

Página oficial →

What is DeepSeek V4-Pro?

DeepSeek V4-Pro is the company’s open flagship: a 1.6-trillion-parameter mixture-of-experts
activating around 49B parameters per token, with a 1M-token context window and MIT-licensed
weights. The API speaks both OpenAI and Anthropic request formats, which makes it unusually
easy to drop into an existing codebase — often a base-URL and key change rather than a
rewrite.

Pricing is $0.435 in / $0.87 out per million tokens, which blends to roughly $0.52 — around
a twentieth of frontier pricing for a model that holds its own on general reasoning. That
ratio, not the parameter count, is why V4-Pro matters. The dual-format API compatibility
compounds it: the switching cost that normally protects incumbent providers largely
disappears, so V4-Pro is a genuine option for teams that would otherwise never evaluate a
Chinese lab’s model. Self-hosting is a data-centre exercise — roughly 800 GB of VRAM at
4-bit, so eight H100 80GBs or more — meaning the open licence here buys auditability and
provider portability rather than a realistic on-premises deployment for most organisations.

DeepSeek V4-Pro pricing: API cost per 1M tokens

Entrada (por cada millón de tokens)$0.435
Salida (por cada millón de tokens)$0.870
Output/input ratio
Blended (4:1 in:out)$0.522 per 1M tokens

What DeepSeek V4-Pro costs per month

Real monthly spend at a 4:1 input-to-output mix — the ratio a typical chat or RAG workload actually produces.

Carga de trabajoTokens/mesCost / month
Proyecto secundario1 millón de tokens de entrada / 0,25 millones de tokens de salida$0.65
Pequeño equipo20 millones de tokens de entrada / 5 millones de tokens de salida$13
Producción200 millones de tokens de entrada / 50 millones de tokens de salida$131

Run your own numbers in the Calculadora de costos de API de IA.

Cheaper alternatives to DeepSeek V4-Pro

ModelosDólares por millón combinadosYou save
DeepSeek V4-Flash abierta$0.168un 68 % más económico

Self-host or pay the API?

DeepSeek V4-Pro is open-weight, so you can run it yourself. It needs ~800 GB of VRAM at 4-bit (Multi-GPU server (e.g. 8× H100 80GB)). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calculadora de autohospedaje frente a API works out the break-even point for your token volume.

Preguntas frecuentes

How much does DeepSeek V4-Pro cost per 1M tokens?

DeepSeek V4-Pro costs $0.435 per 1M input tokens and $0.870 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.522 per 1M tokens.

How much does DeepSeek V4-Pro cost per month?

A small-team workload of 20M input and 5M output tokens a month costs about $13 on DeepSeek V4-Pro. A side project (1M in / 0.25M out) costs roughly $0.65.

What is a cheaper alternative to DeepSeek V4-Pro?

DeepSeek V4-Flash is the strongest cheaper option in our database at $0.168 per 1M blended — about 68% less than DeepSeek V4-Pro. It is also open-weight, so self-hosting is an option.

Can I run DeepSeek V4-Pro locally?

Yes. DeepSeek V4-Pro is open-weight and needs about ~800 GB of VRAM at 4-bit quantisation (Multi-GPU server (e.g. 8× H100 80GB)).

Why does DeepSeek V4-Pro charge more for output than input?

Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. DeepSeek V4-Pro charges 2× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.

See every DeepSeek model priced side by side: DeepSeek API pricing.

Prices are the published list rates for the model's primary API and are reviewed as providers change them. Volume, batch and cached-input discounts are not included. Compare every model side by side in the Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).

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