Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 5.2% higher average benchmark score. Phi-3.5-mini-instruct offers 215.0K more tokens in context window than Gemini 1.0 Pro. Phi-3.5-mini-instruct is $1.80 cheaper per million tokens. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
Gemini 1.0 Pro was developed as Google's initial production-ready multimodal model, designed to handle text and provide strong performance across diverse tasks. Built to serve as a versatile foundation for applications requiring reliable language understanding and generation, it introduced the Gemini architecture to developers and enterprises.
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.
6 months newer

Gemini 1.0 Pro
2024-02-15

Phi-3.5-mini-instruct
Microsoft
2024-08-23
Cost per million tokens (USD)

Gemini 1.0 Pro

Phi-3.5-mini-instruct
Context window and performance specifications
Average performance across 3 common benchmarks

Gemini 1.0 Pro

Phi-3.5-mini-instruct
Gemini 1.0 Pro
2024-02-01
Available providers and their performance metrics

Gemini 1.0 Pro

Phi-3.5-mini-instruct

Gemini 1.0 Pro

Phi-3.5-mini-instruct

Gemini 1.0 Pro

Phi-3.5-mini-instruct
Azure