Multimodal reasoner with 256K context, image and video input, function tools, structured JSON, and thinking on by default.
Alibaba CloudText Generation256K contextReleased Aug 14, 2026Native InferenceNewMultimodal reasoner with 256K context, image and video input, function tools, structured JSON, and thinking on by default.
Supports text, image, and video input, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning_effort (xhigh, medium, low) 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. Open-weight context is 256K; hosted 1M context and official built-in tools are not included.
Also known as Alibaba Cloud Qwen3.8 27B
qwen3-8-27b/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1/completionsPOST/v1beta/models/qwen3-8-27b:generateContentqwen3.8-27bqwen/qwen3-8-27bqwen/qwen3.8-27bLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
Qwen3.8 27B 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 qwen3-8-27b. 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": "qwen3-8-27b",
"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="qwen3-8-27b",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the Qwen3.8 27B API on EmpirioLabs. Defaults apply when a field is omitted.
| Parameter | Type | Default | Range / values | Description |
|---|---|---|---|---|
| temperature | number | 1 | 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. |
| enable_thinking | boolean | true | - | Enable reasoning before answering. |
| reasoning_effort | enum | xhigh | none, low, medium, xhigh | Reasoning effort level. none disables thinking. low, medium, and xhigh select discrete thinking depths. There is no token budget control. |
| 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. |
| frequency_penalty | number | 0 | -2 to 2 | Penalty based on how often a token has already appeared. |
| presence_penalty | number | 0 | -2 to 2 | Penalty for tokens that already appeared in the generated text. |
| 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. |
| top_logprobs | integer | - | 0 to 20 | Return up to this many top token log probabilities. |
Supports text, image, and video input, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning_effort (xhigh, medium, low) 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. Open-weight context is 256K; hosted 1M context and official built-in tools are not included.
On EmpirioLabs, Qwen3.8 27B is billed pay as you go. The live rate card on this page always matches what the API charges.
Qwen3.8 27B supports a 256K-token context window with up to 32,768 output tokens per response.
Yes. Qwen3.8 27B 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 qwen3-8-27b.
Yes. The EmpirioLabs playground runs Qwen3.8 27B 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.
