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Gemini 3.8 Flash Cyber vs Kimi K2.5

Gemini 3.8 Flash Cyber leads the LLM Stats Score 42.4 to 39.1.

Google · Moonshot AI · Updated for 2026

Which is better?

Gemini 3.8 Flash Cyber leads the overall LLM Stats Score 42.4 to 39.1, ranking #46 overall.

In the 1 individual benchmarks reported for both models, Gemini 3.8 Flash Cyber wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 3.8 Flash Cyber

  • overall performance matters — it scores 42.4 and ranks #46 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose Kimi K2.5

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 3.8 Flash Cyber
Google
Kimi K2.5
Moonshot AI
Core performance indexes
LLM Stats Score
42.4
#46
39.1
#58
Coding
35.6
#25
25.2
#65
Agents
31.2
#27
17.8
#65
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.60 / M
Output price
— / M
$3.00 / M
Context window
—
262,100

Individual benchmarks

4 reported for Gemini 3.8 Flash Cyber · 40 for Kimi K2.5

1 shared

Gemini 3.8 Flash Cyber outperforms in 1 benchmarks (CyberGym), while Kimi K2.5 is better at 0 benchmarks.

Gemini 3.8 Flash Cyber significantly outperforms across most benchmarks.

Fri Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

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).

Google
Gemini 3.8 Flash Cyber
Input- tokens
Output- tokens
Moonshot AI
Kimi K2.5
Input262,100 tokens
Output262,100 tokens
Fri Sep 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Kimi K2.5 supports multimodal inputs, whereas Gemini 3.8 Flash Cyber does not.

Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 3.8 Flash Cyber

Text
Images
Audio
Video

Kimi K2.5

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.8 Flash Cyber is licensed under a proprietary license, while Kimi K2.5 uses MIT.

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

Gemini 3.8 Flash Cyber

Proprietary

Closed source

Kimi K2.5

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3.8 Flash Cyber was released on 2026-09-02, while Kimi K2.5 was released on 2026-01-27.

Gemini 3.8 Flash Cyber is 7 months newer than Kimi K2.5.

Gemini 3.8 Flash Cyber

Sep 2, 2026

2 days ago

7mo newer
Kimi K2.5

Jan 27, 2026

7 months ago

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

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 3.8 Flash Cyber and Kimi K2.5 side-by-side, then vote on the output you prefer.

Gemini 3.8 Flash Cyber
✓ Preferred
Kimi K2.5
Open in Playground

FAQ

Common questions about Gemini 3.8 Flash Cyber vs Kimi K2.5.

Which is better, Gemini 3.8 Flash Cyber or Kimi K2.5?

Gemini 3.8 Flash Cyber leads the LLM Stats Score 42.4 to 39.1. Gemini 3.8 Flash Cyber is made by Google and Kimi K2.5 is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 3.8 Flash Cyber compare to Kimi K2.5 in benchmarks?

Gemini 3.8 Flash Cyber scores Gray Swan IPI Benchmark: 94.0%, CyberGym: 86.2%, Google Real-world Vulnerability Discovery: 71.0%, CWE-Bench: 47.2%. Kimi K2.5 scores AIME 2025: 96.1%, HMMT 2025: 95.4%, InfoVQAtest: 92.6%, OCRBench: 92.3%, MathVista-Mini: 90.1%.

What are the context window sizes for Gemini 3.8 Flash Cyber and Kimi K2.5?

Gemini 3.8 Flash Cyber supports an unknown number of tokens and Kimi K2.5 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3.8 Flash Cyber and Kimi K2.5?

Key differences include LLM Stats Score (42.4 vs 39.1), multimodal support (no vs yes), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.8 Flash Cyber and Kimi K2.5?

Gemini 3.8 Flash Cyber is developed by Google and Kimi K2.5 is developed by Moonshot AI.

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