Model Comparison

Kimi K2.5 vs Gemma 4 E2B

Kimi K2.5 significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

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.

Wed May 20 2026 • llm-stats.com

Arena Performance

Human preference votes

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
1.0Tparameters
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
Wed May 20 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

3 months ago

Gemma 4 E2B

Apr 2, 2026

1 months ago

2mo newer

Knowledge Cutoff

When training data ends

Gemma 4 E2B has a documented knowledge cutoff of 2025-01-01, while Kimi K2.5's cutoff date is not specified.

We can confirm Gemma 4 E2B's training data extends to 2025-01-01, but cannot make a direct comparison without Kimi K2.5's cutoff date.

Kimi K2.5

—

Gemma 4 E2B

Jan 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

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

No standout differentiators in the data we have for this pair.

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.

Which is better, Kimi K2.5 or 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.

How does Kimi K2.5 compare to Gemma 4 E2B in benchmarks?

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%.

What are the context window sizes for Kimi K2.5 and Gemma 4 E2B?

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.

What are the main differences between Kimi K2.5 and Gemma 4 E2B?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2.5 and Gemma 4 E2B?

Kimi K2.5 is developed by Moonshot AI and Gemma 4 E2B is developed by Google.