Model Comparison

Gemini 2.0 Flash vs Phi-3.5-MoE-instruct

Gemini 2.0 Flash significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 2.0 Flash outperforms in 3 benchmarks (GPQA, MATH, MMLU-Pro), while Phi-3.5-MoE-instruct is better at 0 benchmarks.

Gemini 2.0 Flash significantly outperforms across most benchmarks.

Sat Apr 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 04 2026 • llm-stats.com
Google
Gemini 2.0 Flash
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Microsoft
Phi-3.5-MoE-instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Gemini 2.0 Flash specifies input context (1,048,576 tokens). Only Gemini 2.0 Flash specifies output context (8,192 tokens).

Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Sat Apr 04 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.0 Flash supports multimodal inputs, whereas Phi-3.5-MoE-instruct does not.

Gemini 2.0 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.0 Flash

Text
Images
Audio
Video

Phi-3.5-MoE-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.0 Flash is licensed under a proprietary license, while Phi-3.5-MoE-instruct uses MIT.

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

Gemini 2.0 Flash

Proprietary

Closed source

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemini 2.0 Flash was released on 2024-12-01, while Phi-3.5-MoE-instruct was released on 2024-08-23.

Gemini 2.0 Flash is 3 months newer than Phi-3.5-MoE-instruct.

Gemini 2.0 Flash

Dec 1, 2024

1.3 years ago

3mo newer
Phi-3.5-MoE-instruct

Aug 23, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a documented knowledge cutoff of 2024-08-01, while Phi-3.5-MoE-instruct's cutoff date is not specified.

We can confirm Gemini 2.0 Flash's training data extends to 2024-08-01, but cannot make a direct comparison without Phi-3.5-MoE-instruct's cutoff date.

Gemini 2.0 Flash

Aug 2024

Phi-3.5-MoE-instruct

—

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher GPQA score (62.1% vs 36.8%)
Higher MATH score (89.7% vs 59.5%)
Higher MMLU-Pro score (76.4% vs 45.3%)
Microsoft
Has open weights
GoogleGemini 2.0 Flash
MicrosoftPhi-3.5-MoE-instruct
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Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 2.0 Flash
Microsoft
Phi-3.5-MoE-instruct

FAQ

Common questions about Gemini 2.0 Flash vs Phi-3.5-MoE-instruct

Gemini 2.0 Flash significantly outperforms across most benchmarks. Gemini 2.0 Flash is made by Google and Phi-3.5-MoE-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.
Gemini 2.0 Flash supports 1.0M tokens and Phi-3.5-MoE-instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemini 2.0 Flash is developed by Google and Phi-3.5-MoE-instruct is developed by Microsoft.