Model Comparison

Kimi K2.5 vs Gemma 4 E2B

Kimi K2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Kimi K2.5 outperforms in 5 benchmarks (GPQA, LiveCodeBench v6, MathVision, MMLU-Pro, MMMU-Pro), while Gemma 4 E2B is better at 0 benchmarks.

Kimi K2.5 significantly outperforms across most benchmarks.

Thu Apr 02 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
Thu Apr 02 2026 • llm-stats.com
Moonshot AI
Kimi K2.5
Input tokens$0.60
Output tokens$2.50
Best providerFireworks
Google
Gemma 4 E2B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

994.9B diff

Kimi K2.5 has 994.9B more parameters than Gemma 4 E2B, making it 19507.8% larger.

Moonshot AI
Kimi K2.5
1000.0Bparameters
Google
Gemma 4 E2B
5.1Bparameters
1000.0B
Kimi K2.5
5.1B
Gemma 4 E2B

Context Window

Maximum input and output token capacity

Only Kimi K2.5 specifies input context (262,100 tokens). Only Kimi K2.5 specifies output context (262,100 tokens).

Moonshot AI
Kimi K2.5
Input262,100 tokens
Output262,100 tokens
Google
Gemma 4 E2B
Input- tokens
Output- tokens
Thu Apr 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Kimi K2.5 and Gemma 4 E2B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Kimi K2.5

Text
Images
Audio
Video

Gemma 4 E2B

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.5 is licensed under MIT, while Gemma 4 E2B uses Apache 2.0.

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

Kimi K2.5

MIT

Open weights

Gemma 4 E2B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2.5 was released on 2026-01-27, while Gemma 4 E2B was released on 2026-04-02.

Gemma 4 E2B is 2 months newer than Kimi K2.5.

Kimi K2.5

Jan 27, 2026

2 months ago

Gemma 4 E2B

Apr 2, 2026

0 days ago

2mo newer

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

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Key Takeaways

Moonshot AI
Larger context window (262,100 tokens)
Higher GPQA score (87.6% vs 43.4%)
Higher LiveCodeBench v6 score (85.0% vs 44.0%)
Higher MathVision score (84.2% vs 52.4%)
Higher MMLU-Pro score (87.1% vs 60.0%)
Higher MMMU-Pro score (78.5% vs 44.2%)
Google

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2.5
Google
Gemma 4 E2B

FAQ

Common questions about Kimi K2.5 vs Gemma 4 E2B

Kimi K2.5 significantly outperforms across most benchmarks. Kimi K2.5 is made by Moonshot AI and Gemma 4 E2B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Kimi K2.5 scores AIME 2025: 96.1%, HMMT 2025: 95.4%, InfoVQAtest: 92.6%, OCRBench: 92.3%, MathVista-Mini: 90.1%. Gemma 4 E2B scores MMMLU: 67.4%, MMLU-Pro: 60.0%, MathVision: 52.4%, MMMU-Pro: 44.2%, LiveCodeBench v6: 44.0%.
Kimi K2.5 supports 262K tokens and Gemma 4 E2B 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 licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Kimi K2.5 is developed by Moonshot AI and Gemma 4 E2B is developed by Google.