Model Comparison

DeepSeek-R1-0528 vs MedGemma 4B IT

Comparing DeepSeek-R1-0528 and MedGemma 4B IT across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1-0528 and MedGemma 4B IT don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

666.7B diff

DeepSeek-R1-0528 has 666.7B more parameters than MedGemma 4B IT, making it 15504.7% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Google
MedGemma 4B IT
4.3Bparameters
671.0B
DeepSeek-R1-0528
4.3B
MedGemma 4B IT

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Google
MedGemma 4B IT
Input- tokens
Output- tokens
Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

MedGemma 4B IT supports multimodal inputs, whereas DeepSeek-R1-0528 does not.

MedGemma 4B IT can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1-0528

Text
Images
Audio
Video

MedGemma 4B IT

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, 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.

DeepSeek-R1-0528

MIT

Open weights

MedGemma 4B IT

Health AI Developer Foundations terms of use

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while MedGemma 4B IT was released on 2025-05-20.

DeepSeek-R1-0528 is 0 month newer than MedGemma 4B IT.

DeepSeek-R1-0528

May 28, 2025

11 months ago

1w newer
MedGemma 4B IT

May 20, 2025

11 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Google
MedGemma 4B IT

FAQ

Common questions about DeepSeek-R1-0528 vs MedGemma 4B IT.

Which is better, DeepSeek-R1-0528 or MedGemma 4B IT?

DeepSeek-R1-0528 (DeepSeek) 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 DeepSeek-R1-0528 compare to MedGemma 4B IT in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. 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 DeepSeek-R1-0528 and MedGemma 4B IT?

DeepSeek-R1-0528 supports 131K 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 DeepSeek-R1-0528 and MedGemma 4B IT?

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

Who makes DeepSeek-R1-0528 and MedGemma 4B IT?

DeepSeek-R1-0528 is developed by DeepSeek and MedGemma 4B IT is developed by Google.