Qwen3.5 4B API

Qwen3.5 4B es un modelo de razonamiento multimodal de bajo costo con contexto 256K, entrada de imagen y vídeo, herramientas de función y salida estructurada.

Alibaba CloudGeneracion de texto256K contextoLanzado Mar 2, 2026Inferencia nativaNuevo

About Qwen3.5 4B

Qwen3.5 4B es un modelo de razonamiento multimodal de bajo costo con contexto 256K, entrada de imagen y vídeo, herramientas de función y salida estructurada.

Soporta texto, imagen y entrada de vídeo, streaming, herramientas de función, salida estructurada JSON, control de semillas y modo de pensamiento por defecto. Use reasoning effort o thinking presupuesto para el pensamiento ligado, o enable thinking=false para respuestas directas. Las lecturas automáticas de caché se facturan a la tasa de entrada de caché cuando se informa por el servicio modelo. No se admiten controles de caché explícitos.

También conocido como Alibaba Cloud Qwen3.5 4B, Qwen3.5-4B, qwen3-5-4b

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Qwen3.5 4B specs

ID del modelo
qwen3-5-4b
Proveedor
Alibaba Cloud
Categoría
Generacion de texto
Released
Mar 2, 2026
Ventana de contexto
256K tokens
Salida máxima
32,768 tokens
Entrada
TextImageVideo
Salida
Text
Endpoints
POST /v1/chat/completions
POST /v1/responses
POST /v1/messages
POST /v1/completions

Qwen3.5 4B API pricing

Live pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.

Tipo
Especificación
Tarifa
Entrada
por señalización rápida 1M
$0.04
Producto
per 1M generados fichas
$0.07
Caché implícita
por fichas de entrada en caché de 1M
$0.02
Web Search (Linkup)
per call when invoked
$0.013
Comparar en la página completa de precios

How to call the Qwen3.5 4B API

Qwen3.5 4B serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id qwen3-5-4b. Get an API key from the EmpirioLabs dashboard.

cURL
curl https://api.empiriolabs.ai/v1/chat/completions \
  -H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-5-4b",
    "messages": [
      {"role": "user", "content": "Write a haiku about the ocean."}
    ]
  }'
Python (OpenAI SDK)
from openai import OpenAI

client = OpenAI(
    base_url="https://api.empiriolabs.ai/v1",
    api_key="YOUR_EMPIRIOLABS_API_KEY",
)

response = client.chat.completions.create(
    model="qwen3-5-4b",
    messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)
Full Qwen3.5 4B API reference

Qwen3.5 4B API parameters

Request parameters supported by the Qwen3.5 4B API on EmpirioLabs. Defaults apply when a field is omitted.

ParámetroTipoPredeterminadoRango / valoresDescripción
temperaturenumber0.70 to 2Sampling temperature. 0 is deterministic and 2 is maximum randomness.
top_pnumber0.950 to 1Nucleus sampling probability mass. Lower values make outputs more focused.
max_tokensinteger40961 to 32768Maximum output tokens.
stopstring--Up to 4 strings where the model will stop generating further tokens.
reasoning_effortenummediumnone, low, medium, high, maxReasoning effort. none disables thinking; low, medium, high, and max set bounded thinking budgets.
enable_thinkingbooleantrue-Enable the model reasoning channel before final output.
thinking_budgetinteger40961024 to 32768Maximum thinking tokens before the final answer. If max_tokens is lower, the service reserves room for the answer.
top_kinteger201 to 200Limit sampling to the top K candidate tokens when supported.
min_pnumber00 to 1Minimum probability threshold for token sampling.
presence_penaltynumber0-2 to 2Penalty for tokens that already appeared in the generated text.
frequency_penaltynumber0-2 to 2Penalty based on how often a token has already appeared.
repetition_penaltynumber10.1 to 2Penalty used by SGLang to reduce repeated text.
seedinteger-0 to 2147483647Optional random seed for reproducible sampling.
logprobsbooleanfalse-Return token log probabilities when supported.
8 more parameters in the docs

Información útil

Soporta texto, imagen y entrada de vídeo, streaming, herramientas de función, salida estructurada JSON, control de semillas y modo de pensamiento por defecto. Use reasoning effort o thinking presupuesto para el pensamiento ligado, o enable thinking=false para respuestas directas. Las lecturas automáticas de caché se facturan a la tasa de entrada de caché cuando se informa por el servicio modelo. No se admiten controles de caché explícitos.

Qwen3.5 4B API: common questions

How much does the Qwen3.5 4B API cost?

On EmpirioLabs, Qwen3.5 4B is billed pay as you go: Input $0.04 por señalización rápida 1M; Producto $0.07 per 1M generados fichas; Caché implícita $0.02 por fichas de entrada en caché de 1M. The live rate card on this page always matches what the API charges.

What is the context window of Qwen3.5 4B?

Qwen3.5 4B supports a 256K-token context window with up to 32,768 output tokens per response.

Is the Qwen3.5 4B API OpenAI-compatible?

Yes. Qwen3.5 4B serves the OpenAI-compatible Chat Completions API, so existing OpenAI SDKs work by pointing base_url at https://api.empiriolabs.ai/v1 and setting the model id to qwen3-5-4b.

Can I try Qwen3.5 4B in the browser before integrating?

Yes. The EmpirioLabs playground runs Qwen3.5 4B in the browser with the same parameters the API exposes, so you can test prompts before writing code.

How do I get a Qwen3.5 4B API key?

Create an EmpirioLabs account, then generate a key under API Keys in the dashboard. Billing is pay-as-you-go credits, so you only pay for the requests you make.

Ready to use better endpoints?

Check out our pricing or reach out if you want your own model deployed on our stack.