DeepSeek-V3.2-Exp vs ERNIE 5.0 Comparison
Comparing DeepSeek-V3.2-Exp and ERNIE 5.0 across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 2 benchmarks (AIME 2025, SimpleQA), while ERNIE 5.0 is better at 3 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro).
ERNIE 5.0 has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Context Window
Maximum input and output token capacity
Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).
Input Capabilities
Supported data types and modalities
ERNIE 5.0 supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
ERNIE 5.0 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
ERNIE 5.0
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while ERNIE 5.0 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while ERNIE 5.0 was released on 2025-01-22.
DeepSeek-V3.2-Exp is 8 months newer than ERNIE 5.0.
Sep 29, 2025
5 months ago
8mo newerJan 22, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek-V3.2-Exp
View detailsDeepSeek
Detailed Comparison
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