Qwen3.8-27B — Specifications
Compilado por Mustafa Ihsan de la documentación publicada por el proveedor · Última actualización
| Desarrollador | Alibaba |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalidad | Text, Image, Video → Text |
| Parámetros | 27B |
| Ventana de contexto | 256K native (up to 1M) |
| Salida máxima | 128 K |
| Licencia | Apache 2.0 (abierta) |
| Pesos abiertos | Sí |
| Lanzado | 2026-08 |
| Precio de entrada | $0.50 /1M |
| Precio de salida | $3.00 /1M |
| Proveedores de API | Alibaba Cloud Model Studio (International), OpenRouter; Ollama (local) |
Ejecútelo localmente
| VRAM (4 bits) | ~18 GB (Ollama 4-bit build) |
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Benchmarks
| Qwen-reported | Terminal Bench 2.1 (Terminus) 73.0; SWE-bench Pro 61.7 (Qwen3.6-27B: 53.5); NL2Repo-Bench 42.3. Prices shown are Alibaba Cloud Model Studio (International). |
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What is Qwen3.8-27B?
Qwen3.8-27B is the dense, 27-billion-parameter member of Alibaba’s Qwen3.8 family and a native vision-language model: it reads text, images and video and writes text. The weights are on Hugging Face under Apache 2.0, and Alibaba added it to Model Studio (International) on 17 August 2026. It has a 262,144-token native context that Qwen says extends to 1,000,000 tokens, and it thinks by default, though thinking can be switched off per request. Alibaba says it improves on Qwen3.6-27B mainly in coding and office tasks; Qwen reports 61.7 on SWE-bench Pro against 53.5 for Qwen3.6-27B.
Alibaba Cloud Model Studio (International) charges $0.50 per million input tokens and $3.00 per million output tokens, with implicit cache hits at $0.10 per million, and serves it with a 1,000,000-token context and up to 131,072 output tokens. Those are the prices on this page. Qwen says a hosted version on its Qwen Cloud service is coming soon.
For local use, Qwen’s own downloads are the BF16 weights, about 55.6 GB, and an FP8 version. Ollama’s library carries 4-bit builds such as qwen3.8:27b-q4_K_M, an 18 GB download, so plan on a 24 GB GPU. It is the modern counterpart to the April 2025 Qwen3 32B and a step up in size from Qwen3 14B, adding image and video input and a much longer context. For Alibaba’s hosted flagship, see Qwen 3.8-Max. Check your quantisation and context length with the Calculadora de VRAM para LLM.
Qwen3.8-27B pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.500 |
|---|---|
| Salida (por cada millón de tokens) | $3.00 |
| Relación salida/entrada | 6× |
| Combinada (4:1 entrada:salida) | $1.00 por 1 millón de tokens |
What Qwen3.8-27B 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 | $1.25 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $25 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $250 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Qwen3.8-27B
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Llama 3.1 8B abierta | $0.0240 | 98% cheaper |
| Mistral NeMo 12B abierta | $0.0292 | 97% más barato |
| Gemma 3 4B abierta | $0.0600 | 94% cheaper |
¿Autoalojarlo o pagar por la API?
Qwen3.8-27B is open-weight, so you can run it yourself. It needs ~18 GB (Ollama 4-bit build) of VRAM at 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 Qwen3.8-27B cost per 1M tokens?
Qwen3.8-27B costs $0.500 per 1M input tokens and $3.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $1.00 per 1M tokens.
How much does Qwen3.8-27B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $25 on Qwen3.8-27B. A side project (1M in / 0.25M out) costs roughly $1.25.
What is a cheaper alternative to Qwen3.8-27B?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 98% less than Qwen3.8-27B. It is also open-weight, so self-hosting is an option.
Can I run Qwen3.8-27B locally?
Yes. Qwen3.8-27B is open-weight and needs about ~18 GB (Ollama 4-bit build) of VRAM at 4-bit quantisation.
Why does Qwen3.8-27B 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. Qwen3.8-27B charges 6× 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).