Qwen3 8B — Especificaciones
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Desarrollador | Alibaba |
|---|---|
| Tipo | LLM (densa) |
| Modalidad | Texto → Texto |
| Parámetros | 8B |
| Ventana de contexto | 128 K |
| Licencia | Apache 2.0 (abierta) |
| Pesos abiertos | Sí |
| Lanzado | 2025 |
| Precio de entrada | $0.04 /1M |
| Precio de salida | $0.14 /1M |
| Proveedores de API | Alibaba, OpenRouter, Ollama |
Ejecútelo localmente
| VRAM (4 bits) | ~5 GB |
|---|---|
| GPU mínima | RTX 3060 8 GB / cualquier GPU de 8 GB |
What is Qwen3 8B?
Qwen3 8B is a small, fast dense model from the Qwen3 family — Apache 2.0, a 128K context,
and about 5 GB of VRAM at 4-bit, which fits an RTX 3060 8GB or any 8 GB card. Hosted pricing
is $0.04 in / $0.14 out per million tokens.
Among models that fit an 8 GB GPU, it is one of the strongest available, and the 128K
context is what separates it from the older generation in the same bracket — Mistral 7B, its
closest historical equivalent, tops out at 32K. That difference decides whether a local
assistant can hold a real document or only a few pages. Apache 2.0 licensing means no
conditions to clear with legal, and the small footprint leaves room on the card for a
generous context or a second process. Treat it as the entry point to local inference: it will
run on hardware you almost certainly already have, and if it proves the use case, Qwen3 14B
and 32B are drop-in upgrades within the same family and licence as your hardware
allows.
Qwen3 8B pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.0400 |
|---|---|
| Salida (por cada millón de tokens) | $0.140 |
| Relación salida/entrada | 3.5× |
| Combinada (4:1 entrada:salida) | $0.0600 por 1 millón de tokens |
What Qwen3 8B 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 | $0.08 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $1.50 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $15 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Qwen3 8B
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Mistral 7B abierta | $0.0220 | 63 % más barato |
| Llama 3.1 8B abierta | $0.0220 | 63 % más barato |
| Mistral NeMo 12B abierta | $0.0240 | 60% cheaper |
¿Autoalojarlo o pagar por la API?
Qwen3 8B is open-weight, so you can run it yourself. It needs ~5 GB of VRAM at 4-bit (RTX 3060 8GB / any 8GB GPU). 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 Qwen3 8B cost per 1M tokens?
Qwen3 8B costs $0.0400 per 1M input tokens and $0.140 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.0600 per 1M tokens.
How much does Qwen3 8B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $1.50 on Qwen3 8B. A side project (1M in / 0.25M out) costs roughly $0.08.
What is a cheaper alternative to Qwen3 8B?
Mistral 7B is the strongest cheaper option in our database at $0.0220 per 1M blended — about 63% less than Qwen3 8B. It is also open-weight, so self-hosting is an option.
Can I run Qwen3 8B locally?
Yes. Qwen3 8B is open-weight and needs about ~5 GB of VRAM at 4-bit quantisation (RTX 3060 8GB / any 8GB GPU).
Why does Qwen3 8B 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. Qwen3 8B charges 3.5× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
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).