o4-mini vs Kimi K3
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | o4-mini | Kimi K3 |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Input Price (1M) | $1.10 | $3.00 |
| Output Price (1M) | $4.40 | $15.00 |
| Context Window | 200,000 | 1,000,000 |
Verdict
o4-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens. Kimi K3 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens. o4-mini is 63% cheaper on input tokens than Kimi K3. For output tokens, o4-mini is the more affordable option at $4.40/1M vs $15.00.
On context window, Kimi K3 supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose o4-mini
- ✓ You need the lowest input token cost ($ 1.10/1M)
- ✓ Your workload is output-heavy — o4-mini generates text cheaper
- ✓ You are already integrated with OpenAI
When to choose Kimi K3
- ✓ You need a larger context window (1,000,000 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 o4-mini cheaper than Kimi K3? ▼
o4-mini is cheaper on input tokens at $1.10/1M vs $3.00/1M for Kimi K3 — a 63% saving.
What is the context window of o4-mini vs Kimi K3? ▼
o4-mini has a 200,000-token context window. Kimi K3 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: o4-mini or Kimi K3? ▼
The best choice depends on your use case. For cost efficiency on input tokens, o4-mini 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.