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Gemini 1.0 Pro vs MedGemma 4B IT

Comparing Gemini 1.0 Pro and MedGemma 4B IT across benchmarks, pricing, and capabilities.

Google · Google · Updated for 2026

Which is better?

Gemini 1.0 Pro and MedGemma 4B IT trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Gemini 1.0 Pro

  • you want predictable pricing at $0.50/M input and $1.50/M output

Choose MedGemma 4B IT

  • you want the most recent training data — it shipped May 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.50 / M
— / M
Output price
$1.50 / M
— / M
Context window
32,760
Released
Feb 2024
May 2025
License
Proprietary
Health AI Developer Foundations terms of use

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 1.0 Pro and MedGemma 4B ITdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind 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
Google
MedGemma 4B IT
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

MedGemma 4B IT supports multimodal inputs, whereas Gemini 1.0 Pro does not.

MedGemma 4B IT 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

MedGemma 4B IT

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while MedGemma 4B IT uses Health AI Developer Foundations terms of use.

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

Gemini 1.0 Pro

Proprietary

Closed source

MedGemma 4B IT

Health AI Developer Foundations terms of use

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while MedGemma 4B IT was released on 2025-05-20.

MedGemma 4B IT is 15 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.5 years ago

MedGemma 4B IT

May 20, 2025

1.3 years ago

1.3yr newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while MedGemma 4B IT'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 MedGemma 4B IT's cutoff date.

Gemini 1.0 Pro

Feb 2024

MedGemma 4B IT

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Gemini 1.0 Pro and MedGemma 4B IT side-by-side, then vote on the output you prefer.

Gemini 1.0 Pro
✓ Preferred
MedGemma 4B IT
Open in Playground

FAQ

Common questions about Gemini 1.0 Pro vs MedGemma 4B IT.

Which is better, Gemini 1.0 Pro or MedGemma 4B IT?

Gemini 1.0 Pro (Google) and MedGemma 4B IT (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 1.0 Pro compare to MedGemma 4B IT in benchmarks?

Gemini 1.0 Pro scores FLEURS: 93.6%, BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%. MedGemma 4B IT scores MIMIC CXR: 88.9%, DermMCQA: 71.8%, PathMCQA: 69.8%, SlakeVQA: 62.3%, VQA-Rad: 49.9%.

What are the context window sizes for Gemini 1.0 Pro and MedGemma 4B IT?

Gemini 1.0 Pro supports 33K tokens and MedGemma 4B IT 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 MedGemma 4B IT?

Key differences include multimodal support (no vs yes), licensing (Proprietary vs Health AI Developer Foundations terms of use). See the full comparison above for benchmark-by-benchmark results.