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Gemini 2.5 Pro vs Kimi K2.7 Code

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Gemini 2.5 Pro Cost
$3.25
Kimi K2.7 Code Cost
$1.75
Kimi K2.7 Code is 46% cheaper
FeatureGemini 2.5 ProKimi K2.7 Code
ProviderGoogleMoonshot AI
Input Price (1M)$1.25$0.95
Output Price (1M)$10.00$4.00
Context Window1,000,000262,144

Verdict

Gemini 2.5 Pro costs $1.25 per 1M input tokens and $10.00 per 1M output tokens. Kimi K2.7 Code costs $0.95 per 1M input tokens and $4.00 per 1M output tokens. Kimi K2.7 Code is 24% cheaper on input tokens than Gemini 2.5 Pro. For output tokens, Kimi K2.7 Code is the more affordable option at $4.00/1M vs $10.00.

On context window, Gemini 2.5 Pro supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose Gemini 2.5 Pro

  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with Google

When to choose Kimi K2.7 Code

  • ✓ You need the lowest input token cost ($ 0.95/1M)
  • ✓ Your workload is output-heavy — Kimi K2.7 Code generates text cheaper
  • ✓ You are already integrated with Moonshot AI

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is Gemini 2.5 Pro cheaper than Kimi K2.7 Code?

Kimi K2.7 Code is cheaper on input tokens at $0.95/1M vs $1.25/1M for Gemini 2.5 Pro — a 24% saving.

What is the context window of Gemini 2.5 Pro vs Kimi K2.7 Code?

Gemini 2.5 Pro has a 1,000,000-token context window. Kimi K2.7 Code has a 262,144-token context window. Gemini 2.5 Pro supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Gemini 2.5 Pro or Kimi K2.7 Code?

The best choice depends on your use case. For cost efficiency on input tokens, Kimi K2.7 Code is the cheaper option. For maximum context length, Gemini 2.5 Pro supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.