DeepSeek V4-Flash — Especificaciones
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Desarrollador | DeepSeek |
|---|---|
| Tipo | LLM (MoE) |
| Modalidad | Texto → Texto |
| Parámetros | 284 000 millones totales / ~13 000 millones activos (MoE) |
| Ventana de contexto | 1 millón |
| Salida máxima | 384 K |
| Licencia | MIT (abierto) |
| Pesos abiertos | Sí |
| Lanzado | 2026-04 |
| Precio de entrada | $0.14 /1M |
| Precio de salida | $0.28 /1M |
| Proveedores de API | DeepSeek, OpenRouter |
Ejecútelo localmente
| VRAM (4 bits) | ~140 GB |
|---|---|
| GPU mínima | 2× H100 de 80 GB (4 bits) |
What is DeepSeek V4-Flash?
DeepSeek V4-Flash is the lighter member of the DeepSeek V4 family — 284B total parameters
with roughly 13B active per token, a 1M-token context window, and open MIT weights. At $0.14
in / $0.28 out per million tokens it is priced for high-volume use, and it is one of the
strongest capability-per-dollar options anywhere in the market.
The number worth internalising is the blended rate of about $0.17 per million tokens
against a frontier model’s $10. That is a ~60× spread for a model that still scores in the
respectable middle of the intelligence rankings, which makes V4-Flash the obvious candidate
for any workload where volume matters more than peak reasoning: bulk classification,
document processing, first-pass summarisation, synthetic data generation, and the retrieval
layer of a RAG pipeline. The 1M context at that price is close to unmatched. Self-hosting is
possible but not casual — about 140 GB of VRAM at 4-bit, so two H100 80GBs — which for most
teams means the API is the practical route and the open weights are insurance rather than a
deployment plan.
DeepSeek V4-Flash pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.140 |
|---|---|
| Salida (por cada millón de tokens) | $0.280 |
| Relación salida/entrada | 2× |
| Combinada (4:1 entrada:salida) | $0.168 por 1 millón de tokens |
What DeepSeek V4-Flash costs per month
Gasto mensual real con una mezcla entrada:salida de 4:1, es decir, la proporción que realmente genera una carga de trabajo típica de chat o RAG.
| Carga de trabajo | Tokens/mes | Coste mensual |
|---|---|---|
| Proyecto secundario | 1 millón de tokens de entrada / 0,25 millones de tokens de salida | $0.21 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $4.20 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $42 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to DeepSeek V4-Flash
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Mistral 7B abierta | $0.0220 | 87% cheaper |
| Llama 3.1 8B abierta | $0.0220 | 87% cheaper |
| Mistral NeMo 12B abierta | $0.0240 | 86% cheaper |
¿Autoalojarlo o pagar por la API?
DeepSeek V4-Flash is open-weight, so you can run it yourself. It needs ~140 GB of VRAM at 4-bit (2× H100 80GB (4-bit)). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calculadora de autohospedaje frente a API calcula el punto de equilibrio para su volumen de tokens.
Preguntas frecuentes
How much does DeepSeek V4-Flash cost per 1M tokens?
DeepSeek V4-Flash costs $0.140 per 1M input tokens and $0.280 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.168 per 1M tokens.
How much does DeepSeek V4-Flash cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $4.20 on DeepSeek V4-Flash. A side project (1M in / 0.25M out) costs roughly $0.21.
What is a cheaper alternative to DeepSeek V4-Flash?
Mistral 7B is the strongest cheaper option in our database at $0.0220 per 1M blended — about 87% less than DeepSeek V4-Flash. It is also open-weight, so self-hosting is an option.
Can I run DeepSeek V4-Flash locally?
Yes. DeepSeek V4-Flash is open-weight and needs about ~140 GB of VRAM at 4-bit quantisation (2× H100 80GB (4-bit)).
Why does DeepSeek V4-Flash 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-Flash 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: Precios de la API de DeepSeek.
Los precios corresponden a las tarifas oficiales publicadas para la API principal del modelo y se revisan periódicamente conforme los proveedores los actualicen. No incluyen descuentos por volumen, procesamiento por lotes ni entradas en caché. Compare todos los modelos uno al lado del otro en la Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).