Model Comparison

Qwen3-Next-80B-A3B-Thinking vs Qwen3 VL 32B InstructWhich is better in 2026?

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

Verdict: Qwen3-Next-80B-A3B-Thinking vs Qwen3 VL 32B Instruct — which is better?

Qwen3-Next-80B-A3B-Thinking (by Alibaba Cloud / Qwen Team) and Qwen3 VL 32B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Qwen3-Next-80B-A3B-Thinking outperforms in 14 benchmarks (AIME 2025, BFCL-v3, GPQA, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 32B Instruct is better at 1 benchmark (Arena-Hard v2). Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.

Choose Qwen3-Next-80B-A3B-Thinking if…

  • you want the strongest raw capability — it leads on 14 of 15 shared benchmarks

Choose Qwen3 VL 32B Instruct if…

  • you want the most recent training data — it shipped Sep 2025
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Performance Benchmarks

Comparative analysis across standard metrics

15 benchmarks

Qwen3-Next-80B-A3B-Thinking outperforms in 14 benchmarks (AIME 2025, BFCL-v3, GPQA, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 32B Instruct is better at 1 benchmark (Arena-Hard v2).

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

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

47.0B diff

Qwen3-Next-80B-A3B-Thinking has 47.0B more parameters than Qwen3 VL 32B Instruct, making it 142.4% larger.

Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
80.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
33.0Bparameters
80.0B
Qwen3-Next-80B-A3B-Thinking
33.0B
Qwen3 VL 32B Instruct

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).

Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Input65,536 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
Input- tokens
Output- tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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

Qwen3-Next-80B-A3B-Thinking

Text
Images
Audio
Video

Qwen3 VL 32B Instruct

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.

Qwen3-Next-80B-A3B-Thinking

Apache 2.0

Open weights

Qwen3 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10, while Qwen3 VL 32B Instruct was released on 2025-09-22.

Qwen3 VL 32B Instruct is 0 month newer than Qwen3-Next-80B-A3B-Thinking.

Qwen3-Next-80B-A3B-Thinking

Sep 10, 2025

9 months ago

Qwen3 VL 32B Instruct

Sep 22, 2025

8 months ago

1w 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

Alibaba Cloud / Qwen Team
Larger context window (65,536 tokens)
Higher AIME 2025 score (87.8% vs 66.2%)
Higher BFCL-v3 score (72.0% vs 70.2%)
Higher GPQA score (77.2% vs 68.9%)
Higher IFEval score (88.9% vs 84.7%)
Higher Include score (78.9% vs 74.0%)
Higher LiveBench 20241125 score (76.6% vs 72.2%)
Higher LiveCodeBench v6 score (68.7% vs 43.8%)
Higher MMLU-Pro score (82.7% vs 78.6%)
Higher MMLU-ProX score (78.7% vs 73.4%)
Higher MMLU-Redux score (92.5% vs 89.8%)
Higher Multi-IF score (77.8% vs 72.0%)
Higher PolyMATH score (56.3% vs 40.5%)
Higher SuperGPQA score (60.8% vs 54.6%)
Higher WritingBench score (84.6% vs 82.9%)
Alibaba Cloud / Qwen Team

Qwen3 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Higher Arena-Hard v2 score (64.7% vs 62.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct

FAQ

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

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

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks. Qwen3-Next-80B-A3B-Thinking 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 Qwen3-Next-80B-A3B-Thinking compare to Qwen3 VL 32B Instruct in benchmarks?

Qwen3-Next-80B-A3B-Thinking scores MMLU-Redux: 92.5%, IFEval: 88.9%, AIME 2025: 87.8%, WritingBench: 84.6%, MMLU-Pro: 82.7%. 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 Qwen3-Next-80B-A3B-Thinking and Qwen3 VL 32B Instruct?

Qwen3-Next-80B-A3B-Thinking supports 66K 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 Qwen3-Next-80B-A3B-Thinking and Qwen3 VL 32B Instruct?

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

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