Model Comparison

Gemma 3n E4B vs Kimi K2 Instruct

Comparing Gemma 3n E4B and Kimi K2 Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E4B and Kimi K2 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
Sat Apr 18 2026 • llm-stats.com
Google
Gemma 3n E4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Moonshot AI
Kimi K2 Instruct
Input tokens$0.50
Output tokens$0.50
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

992.0B diff

Kimi K2 Instruct has 992.0B more parameters than Gemma 3n E4B, making it 12400.0% larger.

Google
Gemma 3n E4B
8.0Bparameters
Moonshot AI
Kimi K2 Instruct
1000.0Bparameters
8.0B
Gemma 3n E4B
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Only Kimi K2 Instruct specifies input context (200,000 tokens). Only Kimi K2 Instruct specifies output context (200,000 tokens).

Google
Gemma 3n E4B
Input- tokens
Output- tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B supports multimodal inputs, whereas Kimi K2 Instruct 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

Kimi K2 Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B is licensed under a proprietary license, while Kimi K2 Instruct uses MIT.

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

Gemma 3n E4B

Proprietary

Closed source

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B was released on 2025-06-26, while Kimi K2 Instruct was released on 2025-07-11.

Kimi K2 Instruct is 1 month newer than Gemma 3n E4B.

Gemma 3n E4B

Jun 26, 2025

9 months ago

Kimi K2 Instruct

Jul 11, 2025

9 months ago

2w newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while Kimi K2 Instruct'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 Kimi K2 Instruct's cutoff date.

Gemma 3n E4B

Jun 2024

Kimi K2 Instruct

—

Outputs Comparison

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Key Takeaways

Google
Supports multimodal inputs
Moonshot AI
Larger context window (200,000 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B
Moonshot AI
Kimi K2 Instruct

FAQ

Common questions about Gemma 3n E4B vs Kimi K2 Instruct

Gemma 3n E4B (Google) and Kimi K2 Instruct (Moonshot AI) 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%. Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.
Gemma 3n E4B supports an unknown number of tokens and Kimi K2 Instruct supports 200K 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 MIT). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B is developed by Google and Kimi K2 Instruct is developed by Moonshot AI.