Model Comparison

Gemma 3n E4B vs Phi-4-multimodal-instruct

Comparing Gemma 3n E4B and Phi-4-multimodal-instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E4B and Phi-4-multimodal-instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sun Apr 19 2026 • llm-stats.com
Google
Gemma 3n E4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Microsoft
Phi-4-multimodal-instruct
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

2.4B diff

Gemma 3n E4B has 2.4B more parameters than Phi-4-multimodal-instruct, making it 42.9% larger.

Google
Gemma 3n E4B
8.0Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
8.0B
Gemma 3n E4B
5.6B
Phi-4-multimodal-instruct

Context Window

Maximum input and output token capacity

Only Phi-4-multimodal-instruct specifies input context (128,000 tokens). Only Phi-4-multimodal-instruct specifies output context (128,000 tokens).

Google
Gemma 3n E4B
Input- tokens
Output- tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Sun Apr 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3n E4B and Phi-4-multimodal-instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 3n E4B

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B is licensed under a proprietary license, while Phi-4-multimodal-instruct uses MIT.

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

Gemma 3n E4B

Proprietary

Closed source

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B was released on 2025-06-26, while Phi-4-multimodal-instruct was released on 2025-02-01.

Gemma 3n E4B is 5 months newer than Phi-4-multimodal-instruct.

Gemma 3n E4B

Jun 26, 2025

9 months ago

4mo newer
Phi-4-multimodal-instruct

Feb 1, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Both models have the same knowledge cutoff date of 2024-06-01.

They should have similar awareness of historical events and information up to this date.

Gemma 3n E4B

Jun 2024

Phi-4-multimodal-instruct

Jun 2024

Outputs Comparison

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Key Takeaways

Google
Microsoft
Larger context window (128,000 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B
Microsoft
Phi-4-multimodal-instruct

FAQ

Common questions about Gemma 3n E4B vs Phi-4-multimodal-instruct

Gemma 3n E4B (Google) and Phi-4-multimodal-instruct (Microsoft) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%. Phi-4-multimodal-instruct scores ScienceQA Visual: 97.5%, DocVQA: 93.2%, MMBench: 86.7%, POPE: 85.6%, OCRBench: 84.4%.
Gemma 3n E4B supports an unknown number of tokens and Phi-4-multimodal-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B is developed by Google and Phi-4-multimodal-instruct is developed by Microsoft.