Top-Tier Reasoning

Qwen 2.5 72B

Qwen 2.5 72B is a powerhouse 72-billion-parameter AI model from Alibaba Cloud's Qwen Team, excelling in coding, math reasoning, multilingual support across 29+ languages, and long-context tasks up to 128K tokens. Unlock its multimodal prowess for structured data, vision-language reasoning, and fine-tuning applications that rival top open-weight models.

32k Context

Top-Tier Intelligence

Dec '23 Knowledge

Available for Chat, Vision, and File Uploads.

Performance Benchmarks

MMLU

85+

HumanEval

N/A

MATH

N/A

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Why use Qwen 2.5 72B?

Superior Reasoning & Math

Competitive zero- and few-shot performance in reasoning, mathematics, and coding, often surpassing larger models

Long-Context Handling

Supports up to 128K token context window and generates long texts over 8K tokens

Multilingual Proficiency

Strong support for over 29 languages with enhanced instruction following and structured data understanding

Capability Examples

Coding Mastery

Write a Python function to solve the N-Queens problem for an 8x8 board, outputting all solutions.

python

print(f"Found {len(solve_n_queens(8))} solutions.") This efficiently solves it using backtracking with bitmasks for diagonals, finding 92 solutions for n=8.

fas fa-code

Multimodal Reasoning

Describe the key elements in this image of a flowchart showing user login process, and suggest one improvement for security. [Imagine image: Flowchart with steps: Start -> Enter credentials -> Validate -> Access granted/denied -> End]

The flowchart depicts a basic login flow: Start leads to "Enter Username & Password," then "Validate Credentials" (checking DB), branching to "Access Granted" or "Access Denied," ending there. Key elements: Sequential arrows, decision diamond at validation, simple ovals for actions. Security improvement: Add a step after validation for multi-factor authentication (MFA) before granting access to prevent credential stuffing attacks.

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