GoogleGemini 3.6 FlashVSMoonshot AI (Kimi)kimi-k2.5

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

If your budget allows, Gemini 3.6 Flash is the superior choice here, offering a clear benchmark advantage while carrying only a moderate price premium (2.5x). We recommend choosing kimi-k2.5 only if you need to optimize costs for very high-volume pipelines.

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Model Specs

Gemini 3.6 Flash

Website

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+8.0%)

58.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+5.4%)

93%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$3.00Input: $1.50 | Output: $7.50

Context WindowLarger

1.05M tokens

Model Specs

kimi-k2.5

Open SourceAPI Available

Website 🤗HF

Benchmarks & Scores

Coding (swe-bench-pro)

50.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)

87.6%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)2.5x cheaper

$1.20Input: $0.60 | Output: $3.00

Context Window

262.14k tokens

Read our data collection methodology

Frequently Asked Questions about Gemini 3.6 Flash vs kimi-k2.5

kimi-k2.5 is cheaper than Gemini 3.6 Flash. kimi-k2.5 has a blended cost of $1.20/1M tokens, which is about 2.5x cheaper than Gemini 3.6 Flash at $3.00/1M tokens.

Gemini 3.6 Flash is better for coding tasks on this benchmark. It scores 58.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to kimi-k2.5 which scores 50.7%.

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