Qwen3 VL 32B Thinking vs Qwen3.5-397B-A17B Comparison
Comparing Qwen3 VL 32B Thinking and Qwen3.5-397B-A17B across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3 VL 32B Thinking outperforms in 0 benchmarks, while Qwen3.5-397B-A17B is better at 9 benchmarks (GPQA, IFEval, Include, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, PolyMATH, SuperGPQA).
Qwen3.5-397B-A17B 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
Qwen3.5-397B-A17B has 364.0B more parameters than Qwen3 VL 32B Thinking, making it 1103.0% larger.
Context Window
Maximum input and output token capacity
Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).
Input Capabilities
Supported data types and modalities
Both Qwen3 VL 32B Thinking and Qwen3.5-397B-A17B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3 VL 32B Thinking
Qwen3.5-397B-A17B
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen3 VL 32B Thinking was released on 2025-09-22, while Qwen3.5-397B-A17B was released on 2026-02-16.
Qwen3.5-397B-A17B is 5 months newer than Qwen3 VL 32B Thinking.
Sep 22, 2025
5 months ago
Feb 16, 2026
3 weeks ago
4mo 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
Qwen3 VL 32B Thinking
View detailsAlibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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