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Gemini 1.0 Pro vs Phi-3.5-vision-instruct

Gemini 1.0 Pro and Phi-3.5-vision-instruct are closely matched at -4.8 and -2.8 on the LLM Stats Score.

Google · Microsoft · Updated for 2026

Which is better?

Gemini 1.0 Pro and Phi-3.5-vision-instruct are closely matched on the overall LLM Stats Score at -4.8 and -2.8.

In the 2 individual benchmarks reported for both models, Gemini 1.0 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 1.0 Pro

  • 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 1.0 Pro
Google
Phi-3.5-vision-instruct
Microsoft
Core performance indexes
LLM Stats Score
-4.8
#335
-2.8
#322
Reasoning
-7.4
#334
-4.2
#321
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.50 / M
— / M
Output price
$1.50 / M
— / M
Context window
32,760
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemini 1.0 Pro
Phi-3.5-vision-instruct
Vision
-8.3#195
-2.9#185
Multimodal
-5.9#156
-0.5#146
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Gemini 1.0 Pro · 9 for Phi-3.5-vision-instruct

2 shared

Gemini 1.0 Pro outperforms in 2 benchmarks (MathVista, MMMU), while Phi-3.5-vision-instruct is better at 0 benchmarks.

Gemini 1.0 Pro significantly outperforms across most benchmarks.

Fri Aug 28 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 1.0 Pro specifies input context (32,760 tokens). Only Gemini 1.0 Pro specifies output context (8,192 tokens).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Microsoft
Phi-3.5-vision-instruct
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Phi-3.5-vision-instruct supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Phi-3.5-vision-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.0 Pro

Text
Images
Audio
Video

Phi-3.5-vision-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 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 1.0 Pro

Proprietary

Closed source

Phi-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Phi-3.5-vision-instruct was released on 2024-08-23.

Phi-3.5-vision-instruct is 6 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.5 years ago

Phi-3.5-vision-instruct

Aug 23, 2024

2.0 years ago

6mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Phi-3.5-vision-instruct's cutoff date is not specified.

We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Phi-3.5-vision-instruct's cutoff date.

Gemini 1.0 Pro

Feb 2024

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 1.0 Pro and Phi-3.5-vision-instruct side-by-side, then vote on the output you prefer.

Gemini 1.0 Pro
✓ Preferred
Phi-3.5-vision-instruct
Open in Playground

FAQ

Common questions about Gemini 1.0 Pro vs Phi-3.5-vision-instruct.

Which is better, Gemini 1.0 Pro or Phi-3.5-vision-instruct?

Gemini 1.0 Pro and Phi-3.5-vision-instruct are closely matched on the LLM Stats Score at -4.8 and -2.8. Gemini 1.0 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 1.0 Pro compare to Phi-3.5-vision-instruct in benchmarks?

Gemini 1.0 Pro scores FLEURS: 93.6%, BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%. 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 1.0 Pro and Phi-3.5-vision-instruct?

Gemini 1.0 Pro supports 33K 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 1.0 Pro and Phi-3.5-vision-instruct?

Key differences include LLM Stats Score (-4.8 vs -2.8), multimodal support (no vs yes), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.0 Pro and Phi-3.5-vision-instruct?

Gemini 1.0 Pro is developed by Google and Phi-3.5-vision-instruct is developed by Microsoft.

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