Model Comparison

Qwen2.5 VL 32B Instruct vs Qwen3-Next-80B-A3B-Thinking

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Qwen2.5 VL 32B Instruct outperforms in 0 benchmarks, while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (GPQA, MMLU-Pro).

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.

Tue May 12 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

46.5B diff

Qwen3-Next-80B-A3B-Thinking has 46.5B more parameters than Qwen2.5 VL 32B Instruct, making it 138.8% larger.

Qwen2.5 VL 32B Instruct

33.5Bparameters

Qwen3-Next-80B-A3B-Thinking

80.0Bparameters

33.5B

Qwen2.5 VL 32B Instruct

80.0B

Qwen3-Next-80B-A3B-Thinking

Context Window

Maximum input and output token capacity

Only Qwen3-Next-80B-A3B-Thinking specifies input context (65,536 tokens). Only Qwen3-Next-80B-A3B-Thinking specifies output context (65,536 tokens).

Qwen2.5 VL 32B Instruct

Input- tokens

Output- tokens

Qwen3-Next-80B-A3B-Thinking

Input65,536 tokens

Output65,536 tokens

Tue May 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Thinking does not.

Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen2.5 VL 32B Instruct

Text

Images

Audio

Video

Qwen3-Next-80B-A3B-Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Qwen3-Next-80B-A3B-Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen2.5 VL 32B Instruct was released on 2025-02-28, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.

Qwen3-Next-80B-A3B-Thinking is 6 months newer than Qwen2.5 VL 32B Instruct.

Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.2 years ago

Qwen3-Next-80B-A3B-Thinking

Sep 10, 2025

8 months ago

6mo 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

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Key Takeaways

Qwen2.5 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Qwen3-Next-80B-A3B-Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (65,536 tokens)

Higher GPQA score (77.2% vs 46.0%)

Higher MMLU-Pro score (82.7% vs 68.8%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen2.5 VL 32B Instruct	Qwen3-Next-80B-A3B-Thinking

FAQ

Common questions about Qwen2.5 VL 32B Instruct vs Qwen3-Next-80B-A3B-Thinking.

Which is better, Qwen2.5 VL 32B Instruct or Qwen3-Next-80B-A3B-Thinking?

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks. Qwen2.5 VL 32B Instruct is made by Alibaba Cloud / Qwen Team and Qwen3-Next-80B-A3B-Thinking 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 VL 32B Instruct compare to Qwen3-Next-80B-A3B-Thinking in benchmarks?

Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%. Qwen3-Next-80B-A3B-Thinking scores MMLU-Redux: 92.5%, IFEval: 88.9%, AIME 2025: 87.8%, WritingBench: 84.6%, MMLU-Pro: 82.7%.

What are the context window sizes for Qwen2.5 VL 32B Instruct and Qwen3-Next-80B-A3B-Thinking?

Qwen2.5 VL 32B Instruct supports an unknown number of tokens and Qwen3-Next-80B-A3B-Thinking supports 66K 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 VL 32B Instruct and Qwen3-Next-80B-A3B-Thinking?

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