Model Comparison
Qwen3.5-397B-A17B vs Qwen2.5 14B Instruct
Qwen3.5-397B-A17B significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.5-397B-A17B outperforms in 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux), while Qwen2.5 14B Instruct is better at 0 benchmarks.
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 382.3B more parameters than Qwen2.5 14B Instruct, making it 2600.7% 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
Qwen3.5-397B-A17B supports multimodal inputs, whereas Qwen2.5 14B Instruct does not.
Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3.5-397B-A17B
Qwen2.5 14B Instruct
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
Qwen3.5-397B-A17B was released on 2026-02-16, while Qwen2.5 14B Instruct was released on 2024-09-19.
Qwen3.5-397B-A17B is 17 months newer than Qwen2.5 14B Instruct.
Feb 16, 2026
2 months ago
1.4yr newerSep 19, 2024
1.6 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
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Qwen3.5-397B-A17B vs Qwen2.5 14B Instruct