QwQ-32B-Preview

completions

bytogetherai

QwQ-32B-Preview

completions

Published by: qwenProvider:

togetherai

QwQ-32B-Preview is an experimental research model developed by the Qwen Team, focused on advancing AI reasoning capabilities.

Released

Nov 28, 2024

Knowledge

Nov 28, 2024

License

Apache-2.0

Context

32768

Input

$1.2 / 1M tokens

Output

$1.2 / 1M tokens

Accepts: text

Returns: text

Released Nov 28, 2024Knowledge Cutoff: Nov 28, 2024License: Apache-2.0

Context: 32768 Input: $1.2 / 1M tokensOutput: $1.2 / 1M tokensAccepts: textReturns: text

Access QwQ-32B-Preview through LangDB AI Gateway

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Benchmark Results for QwQ-32B-Preview

Category Performance Scores:

Academia: Score 46.60 (Top 46% - Rank #155)
Marketing: Score 55.65 (Top 24% - Rank #81)
Science: Score 58.33 (Top 59% - Rank #198)
Writing: Score 52.92 (Top 36% - Rank #121)

Overall Performance: 53.37583333333333 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	45.30	Top 35%	Mathematics
AAII	28.00	Top 60%	General
GPQA	65.20	Top 40%	STEM (Physics, Chemistry, Biology)
HLE	4.80	Top 45%	General Knowledge
LiveCodeBench	33.70	Top 53%	Programming
MATH-500	91.00	Top 35%	Mathematics
MMLU-Pro	64.80	Top 73%	General Knowledge
SciCode	3.80	Top 97%	Scientific

GPQA Score: 65.20 - Graduate-level reasoning benchmark

Model Comparison:

Provider: togetherai

Model Type: completions

Context Size: 32768 tokens

Comparing against 335 models in the database

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

45.3

Mathematics

AAII

28.0

General

GPQA

65.2

STEM (Physics, Chemistry, Biology)

HLE

4.8

General Knowledge

LiveCodeBench

33.7

Programming

MATH-500

91.0

Mathematics

MMLU-Pro

64.8

General Knowledge

SciCode

3.8

Scientific

Metric	AIME	AAII	GPQA	HLE	LiveCodeBench	MATH-500	MMLU-Pro	SciCode
Score	45.3	28.0	65.2	4.8	33.7	91.0	64.8	3.8

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Code Examples

Integration samples and API usage

Code Samples for QwQ-32B-Preview

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="QwQ-32B-Preview",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "QwQ-32B-Preview",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "QwQ-32B-Preview",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: QwQ-32B-Preview

Provider: togetherai

API Endpoint: $https://api.us-east-1.langdb.ai

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QwQ-32B-Preview by togetherai - AI Model Details, Pricing, and Performance Metrics

QwQ-32B-Preview

QwQ-32B-Preview

Access QwQ-32B-Preview through LangDB AI Gateway

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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