Model Comparison

Gemini 2.5 Flash-Lite vs Kimi K2 Base

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 2.5 Flash-Lite outperforms in 1 benchmarks (GPQA), while Kimi K2 Base is better at 1 benchmark (SimpleQA).

Both models are evenly matched across the benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 2.5 Flash-Lite specifies input context (1,048,576 tokens). Only Gemini 2.5 Flash-Lite specifies output context (65,536 tokens).

Google
Gemini 2.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Flash-Lite supports multimodal inputs, whereas Kimi K2 Base does not.

Gemini 2.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.5 Flash-Lite

Text
Images
Audio
Video

Kimi K2 Base

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.5 Flash-Lite is licensed under Creative Commons Attribution 4.0 License, while Kimi K2 Base uses MIT.

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

Gemini 2.5 Flash-Lite

Creative Commons Attribution 4.0 License

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

Gemini 2.5 Flash-Lite was released on 2025-06-17, while Kimi K2 Base was released on 2025-07-11.

Kimi K2 Base is 1 month newer than Gemini 2.5 Flash-Lite.

Gemini 2.5 Flash-Lite

Jun 17, 2025

11 months ago

Kimi K2 Base

Jul 11, 2025

10 months ago

3w newer

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while Kimi K2 Base's cutoff date is not specified.

We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without Kimi K2 Base's cutoff date.

Gemini 2.5 Flash-Lite

Jan 2025

Kimi K2 Base

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Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher GPQA score (64.6% vs 48.1%)
Moonshot AI
Higher SimpleQA score (35.3% vs 10.7%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 2.5 Flash-Lite
Moonshot AI
Kimi K2 Base

FAQ

Common questions about Gemini 2.5 Flash-Lite vs Kimi K2 Base.

Which is better, Gemini 2.5 Flash-Lite or Kimi K2 Base?

Both models are evenly matched across the benchmarks. Gemini 2.5 Flash-Lite is made by Google and Kimi K2 Base is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 2.5 Flash-Lite compare to Kimi K2 Base in benchmarks?

Gemini 2.5 Flash-Lite scores FACTS Grounding: 84.1%, Global-MMLU-Lite: 81.1%, MMMU: 72.9%, GPQA: 64.6%, Vibe-Eval: 51.3%. Kimi K2 Base scores C-Eval: 92.5%, GSM8k: 92.1%, MMLU-redux-2.0: 90.2%, MMLU: 87.8%, TriviaQA: 85.1%.

What are the context window sizes for Gemini 2.5 Flash-Lite and Kimi K2 Base?

Gemini 2.5 Flash-Lite supports 1.0M tokens and Kimi K2 Base 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 Gemini 2.5 Flash-Lite and Kimi K2 Base?

Key differences include multimodal support (yes vs no), licensing (Creative Commons Attribution 4.0 License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.5 Flash-Lite and Kimi K2 Base?

Gemini 2.5 Flash-Lite is developed by Google and Kimi K2 Base is developed by Moonshot AI.