Qwen3.8-27B — Specifications
Compilado por Mustafa Ihsan da documentação publicada pelo fornecedor · Última atualização
| Desenvolvedor | Alibaba |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalidade | Text, Image, Video → Text |
| Parâmetros | 27B |
| Janela de contexto | 256K native (up to 1M) |
| Saída máxima | 128K |
| Licença | Apache 2.0 (aberta) |
| Pesos abertos | Sim |
| Lançado | 2026-08 |
| Preço da entrada | $0.50 /1M |
| Preço da saída | $3.00 /1M |
| Provedores de API | Alibaba Cloud Model Studio (International), OpenRouter; Ollama (local) |
Execute-o localmente
| VRAM (4 bits) | ~18 GB (Ollama 4-bit build) |
|---|
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). |
|---|
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 Qwen3.8-Max. Check your quantisation and context length with the Calculadora de VRAM para LLMs.
Qwen3.8-27B pricing: API cost per 1M tokens
| Entrada (por 1 milhão de tokens) | $0.500 |
|---|---|
| Saída (por 1 milhão de tokens) | $3.00 |
| Razão saída/entrada | 6× |
| Misturada (4:1 entrada:saída) | $1.00 por 1 milhão de tokens |
What Qwen3.8-27B costs per month
Gasto mensal real com uma proporção de entrada para saída de 4:1 — a razão efetivamente gerada por cargas de trabalho típicas de chat ou RAG.
| Carga de trabalho | Tokens/mês | Custo por mês |
|---|---|---|
| Projeto paralelo | 1 milhão de tokens de entrada / 0,25 milhão de tokens de saída | $1.25 |
| Equipe pequena | 20 milhões de tokens de entrada / 5 milhões de tokens de saída | $25 |
| Produção | 200 milhões de tokens de entrada / 50 milhões de tokens de saída | $250 |
Calcule seus próprios números na Calculadora de custos de API de IA.
Cheaper alternatives to Qwen3.8-27B
| Modelo | Custo médio ponderado por US$ 1 milhão | Você economiza |
|---|---|---|
| Llama 3.1 8B aberta | $0.0240 | 98% cheaper |
| Mistral NeMo 12B aberta | $0.0292 | 97% mais barato |
| Gemma 3 4B aberta | $0.0600 | 94% cheaper |
Hospedar localmente ou pagar pela 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 self-hosting vs API calcula o ponto de equilíbrio para seu volume de tokens.
Perguntas frequentes
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.
Os preços correspondem às tarifas listadas oficialmente para a API principal do modelo e são revisados conforme os provedores os atualizam. Descontos por volume, processamento em lote ou entradas em cache não estão incluídos. Compare todos os modelos lado a lado na Banco de dados de modelos de IA ou o Ranking de LLMs.