Model Comparison

Qwen2.5 72B Instruct vs Qwen3 VL 32B Instruct

Qwen3 VL 32B Instruct significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Qwen2.5 72B Instruct outperforms in 0 benchmarks, while Qwen3 VL 32B Instruct is better at 4 benchmarks (GPQA, IFEval, MMLU-Pro, MMLU-Redux).

Qwen3 VL 32B Instruct significantly outperforms across most benchmarks.

Fri May 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

39.7B diff

Qwen2.5 72B Instruct has 39.7B more parameters than Qwen3 VL 32B Instruct, making it 120.3% larger.

Qwen2.5 72B Instruct

72.7Bparameters

Qwen3 VL 32B Instruct

33.0Bparameters

72.7B

Qwen2.5 72B Instruct

33.0B

Qwen3 VL 32B Instruct

Context Window

Maximum input and output token capacity

Only Qwen2.5 72B Instruct specifies input context (131,072 tokens). Only Qwen2.5 72B Instruct specifies output context (8,192 tokens).

Qwen2.5 72B Instruct

Input131,072 tokens

Output8,192 tokens

Qwen3 VL 32B Instruct

Input- tokens

Output- tokens

Fri May 08 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Instruct supports multimodal inputs, whereas Qwen2.5 72B Instruct does not.

Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen2.5 72B Instruct

Text

Images

Audio

Video

Qwen3 VL 32B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Qwen2.5 72B Instruct is licensed under Qwen, while Qwen3 VL 32B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Qwen2.5 72B Instruct

Qwen

Open weights

Qwen3 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen2.5 72B Instruct was released on 2024-09-19, while Qwen3 VL 32B Instruct was released on 2025-09-22.

Qwen3 VL 32B Instruct is 12 months newer than Qwen2.5 72B Instruct.

Qwen2.5 72B Instruct

Sep 19, 2024

1.6 years ago

Qwen3 VL 32B Instruct

Sep 22, 2025

7 months ago

1.0yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Qwen2.5 72B Instruct

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)

Qwen3 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Higher GPQA score (68.9% vs 49.0%)

Higher IFEval score (84.7% vs 84.1%)

Higher MMLU-Pro score (78.6% vs 71.1%)

Higher MMLU-Redux score (89.8% vs 86.8%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen2.5 72B Instruct	Qwen3 VL 32B Instruct

FAQ

Common questions about Qwen2.5 72B Instruct vs Qwen3 VL 32B Instruct.

Which is better, Qwen2.5 72B Instruct or Qwen3 VL 32B Instruct?

Qwen3 VL 32B Instruct significantly outperforms across most benchmarks. Qwen2.5 72B Instruct is made by Alibaba Cloud / Qwen Team and Qwen3 VL 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen2.5 72B Instruct compare to Qwen3 VL 32B Instruct in benchmarks?

Qwen2.5 72B Instruct scores GSM8k: 95.8%, MT-Bench: 93.5%, MBPP: 88.2%, MMLU-Redux: 86.8%, HumanEval: 86.6%. Qwen3 VL 32B Instruct scores DocVQAtest: 96.9%, ScreenSpot: 95.8%, CharXiv-D: 90.5%, MMLU-Redux: 89.8%, AI2D: 89.5%.

What are the context window sizes for Qwen2.5 72B Instruct and Qwen3 VL 32B Instruct?

Qwen2.5 72B Instruct supports 131K tokens and Qwen3 VL 32B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen2.5 72B Instruct and Qwen3 VL 32B Instruct?

Key differences include multimodal support (no vs yes), licensing (Qwen vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.