Ask

Kimi K3 vs Claude Opus 4.8

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Kimi K3 Cost
$6.00
Claude Opus 4.8 Cost
$10.00
Kimi K3 is 40% cheaper
FeatureKimi K3Claude Opus 4.8
ProviderMoonshot AIAnthropic
Input Price (1M)$3.00$5.00
Output Price (1M)$15.00$25.00
Context Window1,000,0001,000,000

Verdict

Kimi K3 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens. Claude Opus 4.8 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens. Kimi K3 is 40% cheaper on input tokens than Claude Opus 4.8. For output tokens, Kimi K3 is the more affordable option at $15.00/1M vs $25.00.

On context window, Kimi K3 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 Kimi K3

  • ✓ You need the lowest input token cost ($ 3.00/1M)
  • ✓ Your workload is output-heavy — Kimi K3 generates text cheaper
  • ✓ You are already integrated with Moonshot AI

When to choose Claude Opus 4.8

  • ✓ You are already integrated with Anthropic

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 Kimi K3 cheaper than Claude Opus 4.8?

Kimi K3 is cheaper on input tokens at $3.00/1M vs $5.00/1M for Claude Opus 4.8 — a 40% saving.

What is the context window of Kimi K3 vs Claude Opus 4.8?

Kimi K3 has a 1,000,000-token context window. Claude Opus 4.8 has a 1,000,000-token context window. Kimi K3 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Kimi K3 or Claude Opus 4.8?

The best choice depends on your use case. For cost efficiency on input tokens, Kimi K3 is the cheaper option. For maximum context length, Kimi K3 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.