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Gemini 1.5 Pro vs Phi-3.5-vision-instruct

Gemini 1.5 Pro leads the LLM Stats Score 12.1 to -3.2.

Google · Microsoft · Updated for 2026

Which is better?

Gemini 1.5 Pro leads the overall LLM Stats Score 12.1 to -3.2, ranking #244 overall.

In the 2 individual benchmarks reported for both models, Gemini 1.5 Pro wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 1.5 Pro

  • overall performance matters — it scores 12.1 and ranks #244 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

Choose Phi-3.5-vision-instruct

  • you want the most recent training data — it shipped Aug 2024
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 1.5 Pro
Google
Phi-3.5-vision-instruct
Microsoft
Core performance indexes
LLM Stats Score
12.1
#244
-3.2
#332
Reasoning
11.9
#237
-4.6
#329
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$2.50 / M
— / M
Output price
$10.00 / M
— / M
Context window
2,097,152
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemini 1.5 Pro
Phi-3.5-vision-instruct
Vision
9.7#123
-3.1#190
Multimodal
13.8#96
-0.6#151
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for Gemini 1.5 Pro · 9 for Phi-3.5-vision-instruct

2 shared

Gemini 1.5 Pro outperforms in 2 benchmarks (MathVista, MMMU), while Phi-3.5-vision-instruct is better at 0 benchmarks.

Gemini 1.5 Pro significantly outperforms across most benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Gemini 1.5 Pro specifies input context (2,097,152 tokens). Only Gemini 1.5 Pro specifies output context (8,192 tokens).

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Microsoft
Phi-3.5-vision-instruct
Input- tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 1.5 Pro and Phi-3.5-vision-instruct support multimodal inputs.

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

Gemini 1.5 Pro

Text
Images
Audio
Video

Phi-3.5-vision-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Pro is licensed under a proprietary license, while Phi-3.5-vision-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-vision-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-vision-instruct was released on 2024-08-23.

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

Gemini 1.5 Pro

May 1, 2024

2.3 years ago

Phi-3.5-vision-instruct

Aug 23, 2024

2.0 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-vision-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-vision-instruct's cutoff date.

Gemini 1.5 Pro

Nov 2023

Phi-3.5-vision-instruct

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 1.5 Pro and Phi-3.5-vision-instruct side-by-side, then vote on the output you prefer.

Gemini 1.5 Pro
✓ Preferred
Phi-3.5-vision-instruct
Open in Playground

FAQ

Common questions about Gemini 1.5 Pro vs Phi-3.5-vision-instruct.

Which is better, Gemini 1.5 Pro or Phi-3.5-vision-instruct?

Gemini 1.5 Pro leads the LLM Stats Score 12.1 to -3.2. Gemini 1.5 Pro is made by Google and Phi-3.5-vision-instruct is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 1.5 Pro compare to Phi-3.5-vision-instruct in benchmarks?

Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%. Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%.

What are the context window sizes for Gemini 1.5 Pro and Phi-3.5-vision-instruct?

Gemini 1.5 Pro supports 2.1M tokens and Phi-3.5-vision-instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.5 Pro and Phi-3.5-vision-instruct?

Key differences include LLM Stats Score (12.1 vs -3.2), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.5 Pro and Phi-3.5-vision-instruct?

Gemini 1.5 Pro is developed by Google and Phi-3.5-vision-instruct is developed by Microsoft.

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