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GPT-4o (2024-11-20) vs Qwen 2.5 72B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GPT-4o (2024-11-20) and Qwen 2.5 72B.

OpenAI

GPT-4o (2024-11-20)

The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded...

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Alibaba

Qwen 2.5 72B

Qwen 2.5 72B is Alibaba Cloud's flagship open-weight large language model from the Qwen 2.5 generation, delivering GPT-4-class performance across general reasoning, coding, mathematics, and multilingual tasks with strong Chinese-language superiority. It supports a 131,072-token context window and is available under a permissive Apache 2.0 license for both research and commercial use, making it one of the most popular open-weight alternatives to Llama for bilingual applications.

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Technical Specifications

SpecificationGPT-4o (2024-11-20)Qwen 2.5 72B
ProviderOpenAIAlibaba
Context Window128,000 tokens131,072 tokens
Agent SuitabilityN/A88/100
Time to First Token (TTFT)N/A280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-11-202025-09-19

API Pricing Comparison

Input Price per Million Tokens

GPT-4o (2024-11-20)

$2.50

Qwen 2.5 72B

$0.40

Output Price per Million Tokens

GPT-4o (2024-11-20)

$10.00

Qwen 2.5 72B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

GPT-4o (2024-11-20) Quirks & Gotchas

No developer gotchas reported.

Qwen 2.5 72B Quirks & Gotchas

  • β–ΈStrong bilingual (ZH/EN) performance β€” best open model for Chinese-language tasks
  • β–ΈSelf-hostable via vLLM or Ollama with 4-bit quantization