Model Comparison

Gemma 3n E4B Instructed vs Llama-3.3 Nemotron Super 49B v1

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemma 3n E4B Instructed outperforms in 0 benchmarks, while Llama-3.3 Nemotron Super 49B v1 is better at 3 benchmarks (AIME 2025, GPQA, MBPP).

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks.

Tue Apr 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
Google
Gemma 3n E4B Instructed
Input tokens$20.00
Output tokens$40.00
Best providerTogether
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

41.9B diff

Llama-3.3 Nemotron Super 49B v1 has 41.9B more parameters than Gemma 3n E4B Instructed, making it 523.8% larger.

Google
Gemma 3n E4B Instructed
8.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
8.0B
Gemma 3n E4B Instructed
49.9B
Llama-3.3 Nemotron Super 49B v1

Context Window

Maximum input and output token capacity

Only Gemma 3n E4B Instructed specifies input context (32,000 tokens). Only Gemma 3n E4B Instructed specifies output context (32,000 tokens).

Google
Gemma 3n E4B Instructed
Input32,000 tokens
Output32,000 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B Instructed supports multimodal inputs, whereas Llama-3.3 Nemotron Super 49B v1 does not.

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

Gemma 3n E4B Instructed

Text
Images
Audio
Video

Llama-3.3 Nemotron Super 49B v1

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed is licensed under a proprietary license, while Llama-3.3 Nemotron Super 49B v1 uses Llama 3.1 Community License.

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

Gemma 3n E4B Instructed

Proprietary

Closed source

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed was released on 2025-06-26, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

Gemma 3n E4B Instructed is 3 months newer than Llama-3.3 Nemotron Super 49B v1.

Gemma 3n E4B Instructed

Jun 26, 2025

9 months ago

3mo newer
Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed has a knowledge cutoff of 2024-06-01, while Llama-3.3 Nemotron Super 49B v1 has a cutoff of 2023-12-31.

Gemma 3n E4B Instructed has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to Llama-3.3 Nemotron Super 49B v1 (2023-12-31).

Gemma 3n E4B Instructed

Jun 2024

6 mo newer
Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

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Key Takeaways

Google
Larger context window (32,000 tokens)
Supports multimodal inputs
NVIDIA
Has open weights
Higher AIME 2025 score (58.4% vs 11.6%)
Higher GPQA score (66.7% vs 23.7%)
Higher MBPP score (91.3% vs 63.6%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B Instructed
NVIDIA
Llama-3.3 Nemotron Super 49B v1

FAQ

Common questions about Gemma 3n E4B Instructed vs Llama-3.3 Nemotron Super 49B v1

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks. Gemma 3n E4B Instructed is made by Google and Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 3n E4B Instructed scores HumanEval: 75.0%, MGSM: 67.0%, MMLU: 64.9%, Global-MMLU-Lite: 64.5%, MBPP: 63.6%. Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%.
Gemma 3n E4B Instructed supports 32K tokens and Llama-3.3 Nemotron Super 49B v1 supports an unknown number of 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 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B Instructed is developed by Google and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.