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gemini-2.5-flash vs kimi-k2.7-code

Side-by-side comparison of gemini-2.5-flash and kimi-k2.7-code: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.

Benchmark comparison

Intelligence Indexreasoning
gemini-2.5-flash27.0%
kimi-k2.7-codeN/A
Coding Indexcoding
gemini-2.5-flash22.2%
kimi-k2.7-codeN/A
Math Indexmath
gemini-2.5-flash73.3%
kimi-k2.7-codeN/A
GPQA Diamondreasoning
gemini-2.5-flash79.0%
kimi-k2.7-codeN/A
AIME 2025math
gemini-2.5-flash73.3%
kimi-k2.7-codeN/A
LiveCodeBenchcoding
gemini-2.5-flash69.5%
kimi-k2.7-codeN/A
Terminal-Bench Hardagentic
gemini-2.5-flash13.6%
kimi-k2.7-codeN/A
τ²-Benchagentic
gemini-2.5-flash31.6%
kimi-k2.7-codeN/A
SciCodecoding
gemini-2.5-flash39.4%
kimi-k2.7-codeN/A
MMLU Proknowledge
gemini-2.5-flash83.2%
kimi-k2.7-codeN/A
Humanity's Last Examreasoning
gemini-2.5-flash11.1%
kimi-k2.7-codeN/A

Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.

Pricing & specifications

gemini-2.5-flashkimi-k2.7-code
Input price / 1M$0.30$0.95
Output price / 1M$2.50$4.00
Context window1.0M tokens262K tokens
Max output66K tokens262K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderGoogle LLC (Gemini API)Moonshot AI

Questions people ask

Is gemini-2.5-flash better than kimi-k2.7-code?
Benchmark data is limited for one or both models. Compare pricing and capabilities in the tables above, and test both on your own workload.
Which is cheaper, gemini-2.5-flash or kimi-k2.7-code?
gemini-2.5-flash is cheaper. gemini-2.5-flash costs $0.30/$2.50 per 1M input/output tokens, while kimi-k2.7-code costs $0.95/$4.00.
Can I use gemini-2.5-flash and kimi-k2.7-code through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "google/gemini-2.5-flash" and "moonshot/kimi-k2.7-code", no other code changes needed.
What are the context windows?
gemini-2.5-flash supports up to 1.0M tokens of context. kimi-k2.7-code supports up to 262K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.

Switch between gemini-2.5-flash and kimi-k2.7-code with one line of code

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