Qwen3 235B-A22B — Especificaciones
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Desarrollador | Alibaba |
|---|---|
| Tipo | LLM (MoE) |
| Modalidad | Texto → Texto |
| Parámetros | 235 mil millones totales / 22 mil millones activos (MoE) |
| Ventana de contexto | 128 K |
| Licencia | Apache 2.0 (abierta) |
| Pesos abiertos | Sí |
| Lanzado | 2025 |
| Precio de entrada | $0.45 /1M |
| Precio de salida | $1.8 /1M |
| Proveedores de API | Alibaba, OpenRouter |
Ejecútelo localmente
| VRAM (4 bits) | ~140 GB |
|---|---|
| GPU mínima | Multi-GPU o Mac con 192 GB |
What is Qwen3 235B-A22B?
Qwen3 235B-A22B is the open flagship of Alibaba’s Qwen3 family — a 235B mixture-of-experts
activating 22B parameters per token, released under Apache 2.0 with a 128K context. Pricing
is $0.45 in / $1.80 out per million tokens; self-hosting needs around 140 GB at 4-bit, which
means a multi-GPU setup or a 192 GB Mac.
The Mac line is not a curiosity. Apple’s unified memory architecture lets a single
workstation address far more model memory than any consumer GPU, so a 192 GB Mac Studio can
hold a 235B model that would otherwise require a multi-GPU server — at a fraction of the
power draw, noise and facilities cost. For a small team that needs frontier-adjacent open
weights on-premises, that is often the only realistic path, and Qwen3 235B-A22B is one of the
strongest models that fits it. Apache 2.0 licensing makes it cleaner to adopt than the Llama 4
models, which carry EU restrictions. The 128K context is narrower than the 1M offered by
newer flagships, which is the main trade-off to weigh.
Qwen3 235B-A22B pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.450 |
|---|---|
| Salida (por cada millón de tokens) | $1.80 |
| Relación salida/entrada | 4× |
| Combinada (4:1 entrada:salida) | $0.720 por 1 millón de tokens |
What Qwen3 235B-A22B 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 | $0.90 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $18 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $180 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Qwen3 235B-A22B
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| DeepSeek V4-Pro abierta | $0.522 | 28% cheaper |
| DeepSeek V4-Flash abierta | $0.168 | 77% cheaper |
| Llama 4 Maverick abierta | $0.320 | 56% cheaper |
¿Autoalojarlo o pagar por la API?
Qwen3 235B-A22B is open-weight, so you can run it yourself. It needs ~140 GB of VRAM at 4-bit (Multi-GPU or Mac 192GB). 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 235B-A22B cost per 1M tokens?
Qwen3 235B-A22B costs $0.450 per 1M input tokens and $1.80 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.720 per 1M tokens.
How much does Qwen3 235B-A22B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $18 on Qwen3 235B-A22B. A side project (1M in / 0.25M out) costs roughly $0.90.
What is a cheaper alternative to Qwen3 235B-A22B?
DeepSeek V4-Pro is the strongest cheaper option in our database at $0.522 per 1M blended — about 28% less than Qwen3 235B-A22B. It is also open-weight, so self-hosting is an option.
Can I run Qwen3 235B-A22B locally?
Yes. Qwen3 235B-A22B is open-weight and needs about ~140 GB of VRAM at 4-bit quantisation (Multi-GPU or Mac 192GB).
Why does Qwen3 235B-A22B 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 235B-A22B charges 4× 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).