+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
GPT-4.1 nano vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 22.2% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
+
+
+
+
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
+
+
+
+
Microsoft
Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
7 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
GPT-4.1 nano
OpenAI
2025-04-14
Performance Metrics
Context window and performance specifications
Average performance across 53 common benchmarks
+
+
+
+
GPT-4.1 nano
Average Score:16.1%
+
+
+
+
Phi-3.5-MoE-instruct
Average Score:38.3%(+22.2%)
+
+
+
+
Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
+
+
+
+
Phi-3.5-MoE-instruct
+
+
+
+
GPT-4.1 nano
Avg Score:16.1%
Providers:1
+
+
+
+
Phi-3.5-MoE-instruct
Avg Score:38.3%(+22.2%)
Providers:0