Unlock the power of QwQ-32B, offering DeepSeek-level performance and blazing-fast reasoning.
QwQ-32B is a powerful reasoning model developed by Alibaba's Qwen team that excels in mathematics and coding tasks. With its extensive context window and advanced reasoning capabilities, this API delivers impressive performance for complex technical applications.
QwQ-32B leverages multi-stage reinforcement learning for advanced reasoning, excelling in math, coding, and problem-solving.
Deploy enterprise-grade AI with unparalleled resource efficiency using QwQ-32B's extended context length of 131,072 tokens.
Enhance your AI with agentic capabilities that adapt reasoning to feedback, enabling critical thinking and seamless tool use for better results.
Claude 3.7 can easily compete with other advanced models like OpenAI's o1 and o3-mini.
QwQ-32B is a more efficient and cost-effective alternative to DeepSeek R1, despite having only 32B parameters compared to DeepSeek's 671B. It matches or outperforms DeepSeek R1 in benchmarks like AIME24 and LiveCodeBench, excelling in math, coding, and problem-solving while using significantly less power. Its advanced reinforcement learning ensures high-quality results with streamlined reasoning and lower token usage. However, DeepSeek R1 remains superior in long-text processing, multilingual tasks, and broad general knowledge.
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Try AI Playground to try QwQ-32B API.
For more information about technical features, please refer to the QwQ-32B model card.
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.aimlapi.com/v1",
api_key="<YOUR_API_KEY>",
)
response = client.chat.completions.create(
model="Qwen/QwQ-32B",
messages=[
{
"role": "system",
"content": "You are an AI assistant who knows everything.",
},
{
"role": "user",
"content": "Tell me, why is the sky blue?"
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")
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