DeepSeek-V3.2-Exp vs Qwen3.5-4B Comparison
Comparing DeepSeek-V3.2-Exp and Qwen3.5-4B across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 3 benchmarks (GPQA, HMMT 2025, MMLU-Pro), while Qwen3.5-4B is better at 0 benchmarks.
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
DeepSeek-V3.2-Exp has 681.0B more parameters than Qwen3.5-4B, making it 17025.0% larger.
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
Qwen3.5-4B supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
Qwen3.5-4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
Qwen3.5-4B
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while Qwen3.5-4B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Qwen3.5-4B was released on 2026-03-02.
Qwen3.5-4B is 5 months newer than DeepSeek-V3.2-Exp.
Sep 29, 2025
5 months ago
Mar 2, 2026
2 weeks ago
5mo newerKnowledge 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
Qwen3.5-4B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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