Model Comparison

ERNIE 4.5 vs Qwen3 VL 30B A3B Instruct

Qwen3 VL 30B A3B Instruct significantly outperforms across most benchmarks. Qwen3 VL 30B A3B Instruct is 4.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

ERNIE 4.5 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 30B A3B Instruct is better at 4 benchmarks (MMLU, MMLU-Pro, MMLU-Redux, SimpleQA).

Qwen3 VL 30B A3B Instruct significantly outperforms across most benchmarks.

Tue May 12 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 30B A3B Instruct costs less

For input processing, ERNIE 4.5 ($0.40/1M tokens) is 2.0x more expensive than Qwen3 VL 30B A3B Instruct ($0.20/1M tokens).

For output processing, ERNIE 4.5 ($4.00/1M tokens) is 5.7x more expensive than Qwen3 VL 30B A3B Instruct ($0.70/1M tokens).

In conclusion, ERNIE 4.5 is more expensive than Qwen3 VL 30B A3B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Tue May 12 2026 • llm-stats.com

ERNIE 4.5

Input tokens$0.40

Output tokens$4.00

Best providerNovita

Qwen3 VL 30B A3B Instruct

Input tokens$0.20

Output tokens$0.70

Best providerNovita

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Model Size

Parameter count comparison

10.0B diff

Qwen3 VL 30B A3B Instruct has 10.0B more parameters than ERNIE 4.5, making it 47.6% larger.

ERNIE 4.5

21.0Bparameters

Qwen3 VL 30B A3B Instruct

31.0Bparameters

21.0B

ERNIE 4.5

31.0B

Qwen3 VL 30B A3B Instruct

Context Window

Maximum input and output token capacity

Qwen3 VL 30B A3B Instruct accepts 131,072 input tokens compared to ERNIE 4.5's 128,000 tokens. ERNIE 4.5 can generate longer responses up to 65,536 tokens, while Qwen3 VL 30B A3B Instruct is limited to 32,768 tokens.

ERNIE 4.5

Input128,000 tokens

Output65,536 tokens

Qwen3 VL 30B A3B Instruct

Input131,072 tokens

Output32,768 tokens

Tue May 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 30B A3B Instruct supports multimodal inputs, whereas ERNIE 4.5 does not.

Qwen3 VL 30B A3B Instruct 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 30B A3B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

ERNIE 4.5 is licensed under a proprietary license, while Qwen3 VL 30B A3B Instruct 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 30B A3B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

ERNIE 4.5 was released on 2025-06-25, while Qwen3 VL 30B A3B Instruct was released on 2025-09-22.

Qwen3 VL 30B A3B Instruct is 3 months newer than ERNIE 4.5.

ERNIE 4.5

Jun 25, 2025

10 months ago

Qwen3 VL 30B A3B Instruct

Sep 22, 2025

7 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

Provider Availability

ERNIE 4.5 is available from Novita. Qwen3 VL 30B A3B Instruct is available from Novita, DeepInfra.

ERNIE 4.5

Novita

Input Price:Input: $0.40/1MOutput Price:Output: $4.00/1M

Qwen3 VL 30B A3B Instruct

Novita

Input Price:Input: $0.20/1MOutput Price:Output: $0.70/1M

Deepinfra

Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

ERNIE 4.5

View details

Baidu

Higher GPQA score (74.0% vs 70.4%)

Qwen3 VL 30B A3B Instruct

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Has open weights

Higher MMLU score (85.0% vs 41.9%)

Higher MMLU-Pro score (77.8% vs 16.0%)

Higher MMLU-Redux score (88.4% vs 43.2%)

Higher SimpleQA score (27.0% vs 1.8%)

Detailed Comparison

AI Model Comparison Table
Feature	ERNIE 4.5	Qwen3 VL 30B A3B Instruct

FAQ

Common questions about ERNIE 4.5 vs Qwen3 VL 30B A3B Instruct.

Which is better, ERNIE 4.5 or Qwen3 VL 30B A3B Instruct?

Qwen3 VL 30B A3B Instruct significantly outperforms across most benchmarks. ERNIE 4.5 is made by Baidu and Qwen3 VL 30B A3B 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 ERNIE 4.5 compare to Qwen3 VL 30B A3B Instruct in benchmarks?

ERNIE 4.5 scores GPQA: 74.0%, ARC-E: 60.7%, PIQA: 55.2%, Winogrande: 51.3%, CLUEWSC: 48.6%. Qwen3 VL 30B A3B Instruct scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, OCRBench: 90.3%, MMLU-Redux: 88.4%, MMBench-V1.1: 87.0%.

Is ERNIE 4.5 cheaper than Qwen3 VL 30B A3B Instruct?

Qwen3 VL 30B A3B Instruct is 2.0x cheaper for input tokens. ERNIE 4.5 costs $0.40/M input and $4.00/M output via novita. Qwen3 VL 30B A3B Instruct costs $0.20/M input and $0.70/M output via novita.

What are the context window sizes for ERNIE 4.5 and Qwen3 VL 30B A3B Instruct?

ERNIE 4.5 supports 128K tokens and Qwen3 VL 30B A3B Instruct supports 131K 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 30B A3B Instruct?

Key differences include context window (128K vs 131K), input pricing ($0.40 vs $0.20/M), 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 30B A3B Instruct?

ERNIE 4.5 is developed by Baidu and Qwen3 VL 30B A3B Instruct is developed by Alibaba Cloud / Qwen Team.