Qwen3.5 4B is a low-cost multimodal reasoning model with 256K context, image and video input, function tools, and structured output.
Alibaba CloudText Generation256K contextReleased Mar 2, 2026Native InferenceNewQwen3.5 4B is a low-cost multimodal reasoning model with 256K context, image and video input, function tools, and structured output.
Supports text, image, and video input, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning_effort or thinking_budget for bounded thinking, or enable_thinking=false for direct answers. Automatic cache reads are billed at the cached-input rate when reported by the model service. Explicit cache controls are not supported.
Also known as Alibaba Cloud Qwen3.5 4B, Qwen3.5-4B, qwen3-5-4b
qwen3-5-4bPOST /v1/chat/completionsPOST /v1/responsesPOST /v1/messagesPOST /v1/completionsLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
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 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."}
]
}'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)Request parameters supported by the Qwen3.5 4B API on EmpirioLabs. Defaults apply when a field is omitted.
| Parameter | Type | Default | Range / values | Description |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 to 2 | Sampling temperature. 0 is deterministic and 2 is maximum randomness. |
| top_p | number | 0.95 | 0 to 1 | Nucleus sampling probability mass. Lower values make outputs more focused. |
| max_tokens | integer | 4096 | 1 to 32768 | Maximum output tokens. |
| stop | string | - | - | Up to 4 strings where the model will stop generating further tokens. |
| reasoning_effort | enum | medium | none, low, medium, high, max | Reasoning effort. none disables thinking; low, medium, high, and max set bounded thinking budgets. |
| enable_thinking | boolean | true | - | Enable the model reasoning channel before final output. |
| thinking_budget | integer | 4096 | 1024 to 32768 | Maximum thinking tokens before the final answer. If max_tokens is lower, the service reserves room for the answer. |
| top_k | integer | 20 | 1 to 200 | Limit sampling to the top K candidate tokens when supported. |
| min_p | number | 0 | 0 to 1 | Minimum probability threshold for token sampling. |
| presence_penalty | number | 0 | -2 to 2 | Penalty for tokens that already appeared in the generated text. |
| frequency_penalty | number | 0 | -2 to 2 | Penalty based on how often a token has already appeared. |
| repetition_penalty | number | 1 | 0.1 to 2 | Penalty used by SGLang to reduce repeated text. |
| seed | integer | - | 0 to 2147483647 | Optional random seed for reproducible sampling. |
| logprobs | boolean | false | - | Return token log probabilities when supported. |
Supports text, image, and video input, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning_effort or thinking_budget for bounded thinking, or enable_thinking=false for direct answers. Automatic cache reads are billed at the cached-input rate when reported by the model service. Explicit cache controls are not supported.
On EmpirioLabs, Qwen3.5 4B is billed pay as you go: Input $0.04 per 1M prompt tokens; Output $0.07 per 1M generated tokens; Implicit cache read $0.02 per 1M cached input tokens. The live rate card on this page always matches what the API charges.
Qwen3.5 4B supports a 256K-token context window with up to 32,768 output tokens per response.
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.
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.
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.
Check out our pricing or reach out if you want your own model deployed on our stack.
