Model Comparison

Gemini 1.5 Pro vs Phi-3.5-mini-instruct

Gemini 1.5 Pro significantly outperforms across most benchmarks. Phi-3.5-mini-instruct is 43.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Gemini 1.5 Pro outperforms in 9 benchmarks (BIG-Bench Hard, GPQA, GSM8k, HellaSwag, HumanEval, MATH, MGSM, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 0 benchmarks.

Gemini 1.5 Pro significantly outperforms across most benchmarks.

Thu Apr 02 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 1.5 Pro ($2.50/1M tokens) is 25.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 100.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, Gemini 1.5 Pro 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
Thu Apr 02 2026 • llm-stats.com
Google
Gemini 1.5 Pro
Input tokens$2.50
Output tokens$10.00
Best providerGoogle
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
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Context Window

Maximum input and output token capacity

Gemini 1.5 Pro accepts 2,097,152 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 1.5 Pro is limited to 8,192 tokens.

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Thu Apr 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 1.5 Pro supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.

Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.5 Pro

Text
Images
Audio
Video

Phi-3.5-mini-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Pro is licensed under a proprietary 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 1.5 Pro

Proprietary

Closed source

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Pro was released on 2024-05-01, while Phi-3.5-mini-instruct was released on 2024-08-23.

Phi-3.5-mini-instruct is 4 months newer than Gemini 1.5 Pro.

Gemini 1.5 Pro

May 1, 2024

1.9 years ago

Phi-3.5-mini-instruct

Aug 23, 2024

1.6 years ago

3mo newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Phi-3.5-mini-instruct's cutoff date is not specified.

We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.

Gemini 1.5 Pro

Nov 2023

Phi-3.5-mini-instruct

—

Provider Availability

Gemini 1.5 Pro is available from Google. Phi-3.5-mini-instruct is available from Azure.

Gemini 1.5 Pro

google logo
Google
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M

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

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Key Takeaways

Google
Larger context window (2,097,152 tokens)
Supports multimodal inputs
Higher BIG-Bench Hard score (89.2% vs 69.0%)
Higher GPQA score (59.1% vs 30.4%)
Higher GSM8k score (90.8% vs 86.2%)
Higher HellaSwag score (93.3% vs 69.4%)
Higher HumanEval score (84.1% vs 62.8%)
Higher MATH score (86.5% vs 48.5%)
Higher MGSM score (87.5% vs 47.9%)
Higher MMLU score (85.9% vs 69.0%)
Higher MMLU-Pro score (75.8% vs 47.4%)
Microsoft
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.5 Pro
Microsoft
Phi-3.5-mini-instruct

FAQ

Common questions about Gemini 1.5 Pro vs Phi-3.5-mini-instruct

Gemini 1.5 Pro significantly outperforms across most benchmarks. Gemini 1.5 Pro 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.
Gemini 1.5 Pro scores XSTest: 98.8%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%, MGSM: 87.5%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.
Phi-3.5-mini-instruct is 25.0x cheaper for input tokens. Gemini 1.5 Pro costs $2.50/M input and $10.00/M output via google. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.
Gemini 1.5 Pro supports 2.1M 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.
Key differences include context window (2.1M vs 128K), input pricing ($2.50 vs $0.10/M), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemini 1.5 Pro is developed by Google and Phi-3.5-mini-instruct is developed by Microsoft.