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Qwen 2.5 72B vs Qwen2.5 VL 72B Instruct

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 Qwen 2.5 72B and Qwen2.5 VL 72B Instruct.

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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Alibaba

Qwen2.5 VL 72B Instruct

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

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Technical Specifications

SpecificationQwen 2.5 72BQwen2.5 VL 72B Instruct
ProviderAlibabaAlibaba
Context Window131,072 tokens131,072 tokens
Agent Suitability88/100N/A
Time to First Token (TTFT)280 msN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-09-192025-02-01

API Pricing Comparison

Input Price per Million Tokens

Qwen 2.5 72B

$0.40

Qwen2.5 VL 72B Instruct

$0.80

Output Price per Million Tokens

Qwen 2.5 72B

$0.80

Qwen2.5 VL 72B Instruct

$1.00

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.

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

Qwen2.5 VL 72B Instruct Quirks & Gotchas

No developer gotchas reported.