qwen/qwen3.8-27b
Release date: 2026-08-14
1,000,000 context · $0.42/M input tokens · $2.55/M output tokens
Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our API:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 0,
});
try {
const response = await client.chat.completions.create({
model: 'qwen/qwen3.8-27b',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 0,
});
try {
const response = await client.chat.completions.create({
model: 'qwen/qwen3.8-27b',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...
This model is imported from OpenRouter metadata and exposed through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.
| Specification | Value |
|---|---|
| Provider | alibaba |
| Model Type | Chat Completions model |
| Architecture | text+image+video->text |
| Context Window | 1000000 tokens |
| Max Input | 934464 tokens |
| Max Output | 65536 tokens |
| Input | Text, Image, Video |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Structured Outputs | Supported |
| OpenRouter Created | August 14, 2026 |
| Token Type | Cost |
|---|---|
| Input | $0.425 per million tokens |
| Output | $2.55 per million tokens |
| Cached Input | $0.085 per million tokens |
| Cache Write (5m) | $0.53125 per million tokens |
Note: Pricing is generated from OpenRouter model metadata. If multiple upstream providers expose different endpoint prices, review and adjust the price before publishing.
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3.8-27b
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3.8-27b",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "qwen/qwen3.8-27b",
"messages": [{"role": "user", "content": "Hello!"}]
}'
Sources: OpenRouter model metadata.
qwen/qwen3.8-27b
Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...
Input
$0.425 /M
Output
$2.55 /M
Context
1000K
Max Output
66K
Vision
Supported
Tool Use
Supported
Access Qwen3.8 27b through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Pricing on WaveSpeedAI: $0.42 per million input tokens and $2.55 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
Qwen3.8 27b supports up to 1000K tokens of context with up to 66K tokens of output per request.
WaveSpeedAI exposes Qwen3.8 27b at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.