GoogleGemini 3.1 ProVSMoonshot AI (Kimi)kimi-k2.6
Our Take
We recommend kimi-k2.6 for a 2.6x API cost saving and superior coding capability, or Gemini 3.1 Pro if your workflow requires peak reasoning. While kimi-k2.6 is more cost-effective, Gemini 3.1 Pro holds a clear reasoning advantage. Choose kimi-k2.6 for code generation, or Gemini 3.1 Pro for complex logical reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Gemini 3.1 Pro scored 54.2%, while kimi-k2.6 scored 58.6%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.1 Pro scored 94.3%, while kimi-k2.6 scored 90.5%.
Cost Efficiency: Gemini 3.1 Pro pricing ($2/M input, $12/M output) is 2.6x cheaper than kimi-k2.6 ($0.95/M input, $4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
54.2%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+3.8%)
94.3%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$4.50Input: $2.00 | Output: $12.00Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+4.4%)
58.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
90.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.6x cheaper
$1.71Input: $0.95 | Output: $4.00Context Window
262.14k tokensFrequently Asked Questions about Gemini 3.1 Pro vs kimi-k2.6
kimi-k2.6 is cheaper than Gemini 3.1 Pro. kimi-k2.6 has a blended cost of $1.71/1M tokens, which is about 2.6x cheaper than Gemini 3.1 Pro at $4.50/1M tokens.
kimi-k2.6 is better for coding tasks on this benchmark. It scores 58.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to Gemini 3.1 Pro which scores 54.2%.
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