Model Comparison

Gemma 3n E2B vs Llama 3.3 70B Instruct

Comparing Gemma 3n E2B and Llama 3.3 70B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E2B and Llama 3.3 70B Instruct 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
Thu Apr 30 2026 • llm-stats.com
Google
Gemma 3n E2B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meta
Llama 3.3 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

62.0B diff

Llama 3.3 70B Instruct has 62.0B more parameters than Gemma 3n E2B, making it 775.0% larger.

Google
Gemma 3n E2B
8.0Bparameters
Meta
Llama 3.3 70B Instruct
70.0Bparameters
8.0B
Gemma 3n E2B
70.0B
Llama 3.3 70B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.3 70B Instruct specifies input context (128,000 tokens). Only Llama 3.3 70B Instruct specifies output context (128,000 tokens).

Google
Gemma 3n E2B
Input- tokens
Output- tokens
Meta
Llama 3.3 70B Instruct
Input128,000 tokens
Output128,000 tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.

Gemma 3n E2B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E2B

Text
Images
Audio
Video

Llama 3.3 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E2B is licensed under a proprietary license, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.

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

Gemma 3n E2B

Proprietary

Closed source

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Release Timeline

When each model was launched

Gemma 3n E2B was released on 2025-06-26, while Llama 3.3 70B Instruct was released on 2024-12-06.

Gemma 3n E2B is 7 months newer than Llama 3.3 70B Instruct.

Gemma 3n E2B

Jun 26, 2025

10 months ago

6mo newer
Llama 3.3 70B Instruct

Dec 6, 2024

1.4 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E2B has a documented knowledge cutoff of 2024-06-01, while Llama 3.3 70B Instruct's cutoff date is not specified.

We can confirm Gemma 3n E2B's training data extends to 2024-06-01, but cannot make a direct comparison without Llama 3.3 70B Instruct's cutoff date.

Gemma 3n E2B

Jun 2024

Llama 3.3 70B Instruct

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Outputs Comparison

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Key Takeaways

Google
Supports multimodal inputs
Meta
Larger context window (128,000 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E2B
Meta
Llama 3.3 70B Instruct

FAQ

Common questions about Gemma 3n E2B vs Llama 3.3 70B Instruct

Gemma 3n E2B (Google) and Llama 3.3 70B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemma 3n E2B scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%. Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%.
Gemma 3n E2B supports an unknown number of tokens and Llama 3.3 70B Instruct supports 128K 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 Llama 3.3 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E2B is developed by Google and Llama 3.3 70B Instruct is developed by Meta.