Model Comparison

ERNIE 4.5 vs Qwen3 VL 32B ThinkingWhich is better in 2026?

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Verdict: ERNIE 4.5 vs Qwen3 VL 32B Thinking — which is better?

ERNIE 4.5 (by Baidu) and Qwen3 VL 32B Thinking (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.

ERNIE 4.5 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 32B Thinking is better at 4 benchmarks (MMLU, MMLU-Pro, MMLU-Redux, SimpleQA). Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Choose ERNIE 4.5 if…

  • you want predictable pricing at $0.40/M input and $4.00/M output

Choose Qwen3 VL 32B Thinking if…

  • you want the strongest raw capability — it leads on 4 of 5 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

ERNIE 4.5 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 32B Thinking is better at 4 benchmarks (MMLU, MMLU-Pro, MMLU-Redux, SimpleQA).

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Mon Jun 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

12.0B diff

Qwen3 VL 32B Thinking has 12.0B more parameters than ERNIE 4.5, making it 57.1% larger.

Baidu
ERNIE 4.5
21.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
33.0Bparameters
21.0B
ERNIE 4.5
33.0B
Qwen3 VL 32B Thinking

Context Window

Maximum input and output token capacity

Only ERNIE 4.5 specifies input context (128,000 tokens). Only ERNIE 4.5 specifies output context (65,536 tokens).

Baidu
ERNIE 4.5
Input128,000 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Mon Jun 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Thinking supports multimodal inputs, whereas ERNIE 4.5 does not.

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

ERNIE 4.5

Text
Images
Audio
Video

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

ERNIE 4.5 is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.

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

ERNIE 4.5

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

ERNIE 4.5 was released on 2025-06-25, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 3 months newer than ERNIE 4.5.

ERNIE 4.5

Jun 25, 2025

11 months ago

Qwen3 VL 32B Thinking

Sep 22, 2025

8 months ago

2mo 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

Baidu
Larger context window (128,000 tokens)
Higher GPQA score (74.0% vs 73.1%)
Alibaba Cloud / Qwen Team

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights
Higher MMLU score (88.7% vs 41.9%)
Higher MMLU-Pro score (82.1% vs 16.0%)
Higher MMLU-Redux score (91.9% vs 43.2%)
Higher SimpleQA score (55.4% vs 1.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Baidu
ERNIE 4.5
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking

FAQ

Common questions about ERNIE 4.5 vs Qwen3 VL 32B Thinking.

Which is better, ERNIE 4.5 or Qwen3 VL 32B Thinking?

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks. ERNIE 4.5 is made by Baidu and Qwen3 VL 32B 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 ERNIE 4.5 compare to Qwen3 VL 32B Thinking in benchmarks?

ERNIE 4.5 scores GPQA: 74.0%, ARC-E: 60.7%, PIQA: 55.2%, Winogrande: 51.3%, CLUEWSC: 48.6%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for ERNIE 4.5 and Qwen3 VL 32B Thinking?

ERNIE 4.5 supports 128K tokens and Qwen3 VL 32B Thinking 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 ERNIE 4.5 and Qwen3 VL 32B Thinking?

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

Who makes ERNIE 4.5 and Qwen3 VL 32B Thinking?

ERNIE 4.5 is developed by Baidu and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

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