Model Comparison

Gemini 2.5 Flash-Lite vs Phi-3.5-mini-instructWhich is better in 2026?

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks. Phi-3.5-mini-instruct is 1.8x cheaper per token.

Verdict: Gemini 2.5 Flash-Lite vs Phi-3.5-mini-instruct — which is better?

Gemini 2.5 Flash-Lite (by Google) and Phi-3.5-mini-instruct (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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

On price, Phi-3.5-mini-instruct is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 2.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 2.5 Flash-Lite if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jun 2025

Choose Phi-3.5-mini-instruct if…

  • cost matters — it's about 1.8x cheaper per token

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

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

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Phi-3.5-mini-instruct costs less

For input processing, Gemini 2.5 Flash-Lite ($0.10/1M tokens) costs the same as Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, Gemini 2.5 Flash-Lite ($0.40/1M tokens) is 4.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, Gemini 2.5 Flash-Lite is more expensive than Phi-3.5-mini-instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 28 2026 • llm-stats.com
Google
Gemini 2.5 Flash-Lite
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 2.5 Flash-Lite accepts 1,048,576 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Phi-3.5-mini-instruct can generate longer responses up to 128,000 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.

Google
Gemini 2.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Tue Jul 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Flash-Lite supports multimodal inputs, whereas Phi-3.5-mini-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-mini-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-mini-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-mini-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-mini-instruct was released on 2024-08-23.

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

Gemini 2.5 Flash-Lite

Jun 17, 2025

1.1 years ago

9mo newer
Phi-3.5-mini-instruct

Aug 23, 2024

1.9 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-mini-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-mini-instruct's cutoff date.

Gemini 2.5 Flash-Lite

Jan 2025

Phi-3.5-mini-instruct

—

Provider Availability

Gemini 2.5 Flash-Lite is available from Google. Phi-3.5-mini-instruct is available from Azure.

Gemini 2.5 Flash-Lite

google logo
Google
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher GPQA score (64.6% vs 30.4%)
Microsoft
Less expensive output tokens

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 2.5 Flash-Lite and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.

Gemini 2.5 Flash-Lite
✓ Preferred
Phi-3.5-mini-instruct
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 2.5 Flash-Lite
Microsoft
Phi-3.5-mini-instruct

FAQ

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

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

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is made by Google and Phi-3.5-mini-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-mini-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-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is Gemini 2.5 Flash-Lite cheaper than Phi-3.5-mini-instruct?

Both models cost $0.10 per million input tokens.

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

Gemini 2.5 Flash-Lite supports 1.0M tokens and Phi-3.5-mini-instruct supports 128K 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-mini-instruct?

Key differences include context window (1.0M vs 128K), 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-mini-instruct?

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

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