Model Comparison

Gemini 2.5 Flash-Lite vs Phi-3.5-MoE-instruct

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 2.5 Flash-Lite outperforms in 1 benchmarks (GPQA), while Phi-3.5-MoE-instruct is better at 0 benchmarks.

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks.

Fri May 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 2.5 Flash-Lite specifies input context (1,048,576 tokens). Only Gemini 2.5 Flash-Lite specifies output context (65,536 tokens).

Google
Gemini 2.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Fri May 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Flash-Lite supports multimodal inputs, whereas Phi-3.5-MoE-instruct does not.

Gemini 2.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.5 Flash-Lite

Text
Images
Audio
Video

Phi-3.5-MoE-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.5 Flash-Lite is licensed under Creative Commons Attribution 4.0 License, while Phi-3.5-MoE-instruct uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 2.5 Flash-Lite

Creative Commons Attribution 4.0 License

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemini 2.5 Flash-Lite was released on 2025-06-17, while Phi-3.5-MoE-instruct was released on 2024-08-23.

Gemini 2.5 Flash-Lite is 10 months newer than Phi-3.5-MoE-instruct.

Gemini 2.5 Flash-Lite

Jun 17, 2025

11 months ago

9mo newer
Phi-3.5-MoE-instruct

Aug 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while Phi-3.5-MoE-instruct's cutoff date is not specified.

We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without Phi-3.5-MoE-instruct's cutoff date.

Gemini 2.5 Flash-Lite

Jan 2025

Phi-3.5-MoE-instruct

Outputs Comparison

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Key Takeaways

Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher GPQA score (64.6% vs 36.8%)

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 2.5 Flash-Lite
Microsoft
Phi-3.5-MoE-instruct

FAQ

Common questions about Gemini 2.5 Flash-Lite vs Phi-3.5-MoE-instruct.

Which is better, Gemini 2.5 Flash-Lite or Phi-3.5-MoE-instruct?

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is made by Google and Phi-3.5-MoE-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 2.5 Flash-Lite compare to Phi-3.5-MoE-instruct in benchmarks?

Gemini 2.5 Flash-Lite scores FACTS Grounding: 84.1%, Global-MMLU-Lite: 81.1%, MMMU: 72.9%, GPQA: 64.6%, Vibe-Eval: 51.3%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.

What are the context window sizes for Gemini 2.5 Flash-Lite and Phi-3.5-MoE-instruct?

Gemini 2.5 Flash-Lite supports 1.0M tokens and Phi-3.5-MoE-instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 2.5 Flash-Lite and Phi-3.5-MoE-instruct?

Key differences include multimodal support (yes vs no), licensing (Creative Commons Attribution 4.0 License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.5 Flash-Lite and Phi-3.5-MoE-instruct?

Gemini 2.5 Flash-Lite is developed by Google and Phi-3.5-MoE-instruct is developed by Microsoft.