Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 27.9% higher average benchmark score. Gemini 2.0 Flash-Lite offers 800.8K more tokens in context window than Phi-3.5-mini-instruct. Both models have similar pricing. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, Gemini 2.0 Flash-Lite is the stronger choice for coding tasks.
Gemini 2.0 Flash Lite was created as an even more efficient variant of Gemini 2.0 Flash, designed for applications where minimal latency and maximum cost-effectiveness are essential. Built to bring next-generation multimodal capabilities to resource-constrained deployments, it optimizes for speed and affordability.
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.
5 months newer

Phi-3.5-mini-instruct
Microsoft
2024-08-23

Gemini 2.0 Flash-Lite
2025-02-05
Cost per million tokens (USD)

Gemini 2.0 Flash-Lite

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

Gemini 2.0 Flash-Lite

Phi-3.5-mini-instruct
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics

Gemini 2.0 Flash-Lite

Phi-3.5-mini-instruct

Gemini 2.0 Flash-Lite

Phi-3.5-mini-instruct

Gemini 2.0 Flash-Lite

Phi-3.5-mini-instruct
Azure