Model Comparison

Gemma 3n E4B Instructed vs Phi-3.5-mini-instruct

Both models are evenly matched across the benchmarks. Phi-3.5-mini-instruct is 250.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Gemma 3n E4B Instructed outperforms in 3 benchmarks (HumanEval, MGSM, MMLU-Pro), while Phi-3.5-mini-instruct is better at 3 benchmarks (GPQA, MBPP, MMLU).

Both models are evenly matched across the benchmarks.

Wed Apr 29 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, Gemma 3n E4B Instructed ($20.00/1M tokens) is 200.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 400.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, Gemma 3n E4B Instructed 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
Wed Apr 29 2026 • llm-stats.com
Google
Gemma 3n E4B Instructed
Input tokens$20.00
Output tokens$40.00
Best providerTogether
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

4.2B diff

Gemma 3n E4B Instructed has 4.2B more parameters than Phi-3.5-mini-instruct, making it 110.5% larger.

Google
Gemma 3n E4B Instructed
8.0Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
8.0B
Gemma 3n E4B Instructed
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

Phi-3.5-mini-instruct accepts 128,000 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. Phi-3.5-mini-instruct can generate longer responses up to 128,000 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.

Google
Gemma 3n E4B Instructed
Input32,000 tokens
Output32,000 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Wed Apr 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B Instructed supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.

Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E4B Instructed

Text
Images
Audio
Video

Phi-3.5-mini-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed 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.

Gemma 3n E4B Instructed

Proprietary

Closed source

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed was released on 2025-06-26, while Phi-3.5-mini-instruct was released on 2024-08-23.

Gemma 3n E4B Instructed is 10 months newer than Phi-3.5-mini-instruct.

Gemma 3n E4B Instructed

Jun 26, 2025

10 months ago

10mo newer
Phi-3.5-mini-instruct

Aug 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Phi-3.5-mini-instruct's cutoff date is not specified.

We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.

Gemma 3n E4B Instructed

Jun 2024

Phi-3.5-mini-instruct

—

Provider Availability

Gemma 3n E4B Instructed is available from Together. Phi-3.5-mini-instruct is available from Azure.

Gemma 3n E4B Instructed

together logo
Together
Input Price:Input: $20.00/1MOutput Price:Output: $40.00/1M

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
Supports multimodal inputs
Higher HumanEval score (75.0% vs 62.8%)
Higher MGSM score (67.0% vs 47.9%)
Higher MMLU-Pro score (50.6% vs 47.4%)
Microsoft
Larger context window (128,000 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (30.4% vs 23.7%)
Higher MBPP score (69.6% vs 63.6%)
Higher MMLU score (69.0% vs 64.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B Instructed
Microsoft
Phi-3.5-mini-instruct

FAQ

Common questions about Gemma 3n E4B Instructed vs Phi-3.5-mini-instruct

Both models are evenly matched across the benchmarks. Gemma 3n E4B Instructed 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.
Gemma 3n E4B Instructed scores HumanEval: 75.0%, MGSM: 67.0%, MMLU: 64.9%, Global-MMLU-Lite: 64.5%, MBPP: 63.6%. 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 200.0x cheaper for input tokens. Gemma 3n E4B Instructed costs $20.00/M input and $40.00/M output via together. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.
Gemma 3n E4B Instructed supports 32K 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 (32K vs 128K), input pricing ($20.00 vs $0.10/M), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B Instructed is developed by Google and Phi-3.5-mini-instruct is developed by Microsoft.