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o1 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 o1 and Qwen 2.5 72B.

OpenAI

o1

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

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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

Specificationo1Qwen 2.5 72B
ProviderOpenAIAlibaba
Context Window200,000 tokens131,072 tokens
Agent Suitability88/10088/100
Time to First Token (TTFT)2500 ms280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-12-172025-09-19

API Pricing Comparison

Input Price per Million Tokens

o1

$15.00

Qwen 2.5 72B

$0.40

Output Price per Million Tokens

o1

$60.00

Qwen 2.5 72B

$0.80

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Benchmark Performance Metrics

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

MMLUGeneral knowledge & multi-task understanding
9180.0%vsN/A
o1
Qwen 2.5 72B
HumanEvalPython coding & logic synthesis
9450.0%vsN/A
o1
Qwen 2.5 72B
MATHComplex mathematical problem solving
9480.0%vsN/A
o1
Qwen 2.5 72B
GPQAGraduate-level expert reasoning
7830.0%vsN/A
o1
Qwen 2.5 72B
HellaSwagCommonsense reasoning and inference
9200.0%vsN/A
o1
Qwen 2.5 72B
MT-BenchMulti-turn conversation flow quality
940.0%vsN/A
o1
Qwen 2.5 72B

o1 Quirks & Gotchas

  • โ–ธReasoning model โ€” high latency by design, not for real-time use
  • โ–ธBest for complex math/code reasoning where accuracy > speed
  • โ–ธUse o3-mini when you need reasoning with lower latency

Qwen 2.5 72B Quirks & Gotchas

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