+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Phi-3.5-mini-instruct vs Qwen2.5 7B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 7B Instruct leads with 13.4% higher average benchmark score. Phi-3.5-mini-instruct offers 116.7K more tokens in context window than Qwen2.5 7B Instruct. Both models have similar pricing. Overall, Qwen2.5 7B 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
Qwen 2.5 7B was created as an efficient instruction-tuned model, designed to provide capable performance with just 7 billion parameters. Built for applications requiring reliable language understanding with minimal computational overhead, it serves as an accessible entry point to the Qwen 2.5 family.
27 days newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Qwen2.5 7B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
+
+
+
+
+
+
+
+
+
+
+
+
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.40 cheaper)
+
+
+
+
Qwen2.5 7B Instruct
Input:$0.30
Output:$0.30
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
+
+
+
+
Phi-3.5-mini-instruct
Average Score:54.6%
+
+
+
+
Qwen2.5 7B Instruct
Average Score:68.0%(+13.4%)
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 7B Instruct
+
+
+
+
Phi-3.5-mini-instruct
Avg Score:54.6%
Providers:1
+
+
+
+
Qwen2.5 7B Instruct
Avg Score:68.0%(+13.4%)
Providers:1