Qwen3 & Kimi K3 API

Model Comparison

Model	Provider	Context	Speed	Ideal Use Case
qwen3.6-flash	Alibaba	32K	⚡⚡⚡	Fast completions, chatbots
qwen3-flash	Alibaba	32K	⚡⚡⚡	Quick responses, classification
qwen-plus	Alibaba	128K	⚡⚡	General purpose, content
qwen-max	Alibaba	128K	⚡	Complex reasoning, analysis
kimi-k3	Moonshot	128K	⚡⚡	Long documents, research

Quick Start — Python

from openai import OpenAI

client = OpenAI(
    base_url="https://eaf9553505eeb8f5-115-190-107-107.serveousercontent.com/v1",
    api_key="your-api-key"
)

# Use Qwen3
response = client.chat.completions.create(
    model="qwen3.6-flash",  # Fast and cheap
    messages=[
        {"role": "user", "content": "Summarize this document..."}
    ]
)
print(response.choices[0].message.content)

# Use Kimi K3 for long context tasks
response = client.chat.completions.create(
    model="kimi-k3",  # Great for long documents
    messages=[
        {"role": "user", "content": "Analyze this 100-page report..."}
    ]
)

Quick Start — JavaScript

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://eaf9553505eeb8f5-115-190-107-107.serveousercontent.com/v1',
  apiKey: 'your-api-key'
});

// Switch models with a single parameter
const qwen = await client.chat.completions.create({
  model: 'qwen-plus',
  messages: [{ role: 'user', content: 'Hello from Qwen!' }]
});

const kimi = await client.chat.completions.create({
  model: 'kimi-k3',
  messages: [{ role: 'user', content: 'Hello from Kimi!' }]
});

Why Use Our Gateway?