Model Comparison

Gemma 3n E4B vs GPT OSS 120B High

Comparing Gemma 3n E4B and GPT OSS 120B High across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E4B and GPT OSS 120B High don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Google
Gemma 3n E4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
OpenAI
GPT OSS 120B High
Input tokens$0.10
Output tokens$0.50
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

108.8B diff

GPT OSS 120B High has 108.8B more parameters than Gemma 3n E4B, making it 1360.0% larger.

Google
Gemma 3n E4B
8.0Bparameters
OpenAI
GPT OSS 120B High
116.8Bparameters
8.0B
Gemma 3n E4B
116.8B
GPT OSS 120B High

Context Window

Maximum input and output token capacity

Only GPT OSS 120B High specifies input context (131,072 tokens). Only GPT OSS 120B High specifies output context (131,072 tokens).

Google
Gemma 3n E4B
Input- tokens
Output- tokens
OpenAI
GPT OSS 120B High
Input131,072 tokens
Output131,072 tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B supports multimodal inputs, whereas GPT OSS 120B High does not.

Gemma 3n E4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E4B

Text
Images
Audio
Video

GPT OSS 120B High

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B is licensed under a proprietary license, while GPT OSS 120B High uses Apache 2.0.

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

Gemma 3n E4B

Proprietary

Closed source

GPT OSS 120B High

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B was released on 2025-06-26, while GPT OSS 120B High was released on 2025-08-05.

GPT OSS 120B High is 1 month newer than Gemma 3n E4B.

Gemma 3n E4B

Jun 26, 2025

9 months ago

GPT OSS 120B High

Aug 5, 2025

8 months ago

1mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while GPT OSS 120B High's cutoff date is not specified.

We can confirm Gemma 3n E4B's training data extends to 2024-06-01, but cannot make a direct comparison without GPT OSS 120B High's cutoff date.

Gemma 3n E4B

Jun 2024

GPT OSS 120B High

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Outputs Comparison

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Key Takeaways

Google
Supports multimodal inputs
OpenAI
Larger context window (131,072 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B
OpenAI
GPT OSS 120B High

FAQ

Common questions about Gemma 3n E4B vs GPT OSS 120B High

Gemma 3n E4B (Google) and GPT OSS 120B High (OpenAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%. GPT OSS 120B High scores AIME 2025: 92.5%, MMMLU: 83.8%, LiveCodeBench v6: 81.9%, GPQA: 80.9%, MMLU-Pro: 80.7%.
Gemma 3n E4B supports an unknown number of tokens and GPT OSS 120B High supports 131K 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 Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B is developed by Google and GPT OSS 120B High is developed by OpenAI.