+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Phi-3.5-mini-instruct vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 32B Instruct leads with 20.5% higher average benchmark score. Qwen2.5 VL 32B Instruct supports multimodal inputs. Overall, Qwen2.5 VL 32B Instruct is the stronger choice for coding tasks.
+
+
+
+
Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
+
+
+
+
Alibaba Cloud / Qwen Team
Qwen2.5-VL 32B was developed as a mid-sized vision-language model, designed to balance multimodal capability with practical deployment considerations. Built with 32 billion parameters for vision and language integration, it serves applications requiring strong visual understanding without flagship-scale resources.
6 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Qwen2.5 VL 32B Instruct
Alibaba Cloud / Qwen Team
2025-02-28
+
+
+
+
+
+
+
+
+
+
+
+
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
+
+
+
+
Phi-3.5-mini-instruct
Average Score:54.6%
+
+
+
+
Qwen2.5 VL 32B Instruct
Average Score:75.1%(+20.5%)
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Phi-3.5-mini-instruct
1 providers
Azure
Throughput: 23 tok/s
Latency: 0.52ms
+
+
+
+
Qwen2.5 VL 32B Instruct
+
+
+
+
Phi-3.5-mini-instruct
Avg Score:54.6%
Providers:1
+
+
+
+
Qwen2.5 VL 32B Instruct
Avg Score:75.1%(+20.5%)
Providers:0