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o3-mini vs Kimi K2.7 Code

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

o3-mini Cost
$1.98
Kimi K2.7 Code Cost
$1.75
Kimi K2.7 Code is 12% cheaper
Featureo3-miniKimi K2.7 Code
ProviderOpenAIMoonshot AI
Input Price (1M)$1.10$0.95
Output Price (1M)$4.40$4.00
Context Window200,000262,144

Verdict

o3-mini costs $1.10 per 1M input tokens and $4.40 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 14% cheaper on input tokens than o3-mini. For output tokens, Kimi K2.7 Code is the more affordable option at $4.00/1M vs $4.40.

On context window, Kimi K2.7 Code supports 262,144 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 o3-mini

  • ✓ You are already integrated with OpenAI

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 need a larger context window (262,144 tokens)
  • ✓ 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 o3-mini cheaper than Kimi K2.7 Code?

Kimi K2.7 Code is cheaper on input tokens at $0.95/1M vs $1.10/1M for o3-mini — a 14% saving.

What is the context window of o3-mini vs Kimi K2.7 Code?

o3-mini has a 200,000-token context window. Kimi K2.7 Code has a 262,144-token context window. Kimi K2.7 Code supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: o3-mini 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, Kimi K2.7 Code supports 262,144 tokens. Use the comparison table above to find the right fit for your workload.