Model Comparison

Gemini Diffusion vs Phi-4-multimodal-instruct

Comparing Gemini Diffusion 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

Gemini Diffusion 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
Mon Apr 13 2026 • llm-stats.com
Google
Gemini Diffusion
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→

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
Gemini Diffusion
Input- tokens
Output- tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Mon Apr 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Phi-4-multimodal-instruct supports multimodal inputs, whereas Gemini Diffusion does not.

Phi-4-multimodal-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini Diffusion

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini Diffusion 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.

Gemini Diffusion

Proprietary

Closed source

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while Phi-4-multimodal-instruct was released on 2025-02-01.

Gemini Diffusion is 4 months newer than Phi-4-multimodal-instruct.

Gemini Diffusion

May 20, 2025

10 months ago

3mo newer
Phi-4-multimodal-instruct

Feb 1, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Gemini Diffusion's cutoff date is not specified.

We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without Gemini Diffusion's cutoff date.

Gemini Diffusion

—

Phi-4-multimodal-instruct

Jun 2024

Outputs Comparison

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Key Takeaways

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

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
Microsoft
Phi-4-multimodal-instruct

FAQ

Common questions about Gemini Diffusion vs Phi-4-multimodal-instruct

Gemini Diffusion (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.
Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. Phi-4-multimodal-instruct scores ScienceQA Visual: 97.5%, DocVQA: 93.2%, MMBench: 86.7%, POPE: 85.6%, OCRBench: 84.4%.
Gemini Diffusion 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 multimodal support (no vs yes), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemini Diffusion is developed by Google and Phi-4-multimodal-instruct is developed by Microsoft.