GPT-5.2 Pro vs Kimi K2.6
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-5.2 Pro | Kimi K2.6 |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Input Price (1M) | $21.00 | $0.95 |
| Output Price (1M) | $168.00 | $4.00 |
| Context Window | 128,000 | 262,144 |
Verdict
GPT-5.2 Pro costs $21.00 per 1M input tokens and $168.00 per 1M output tokens. Kimi K2.6 costs $0.95 per 1M input tokens and $4.00 per 1M output tokens. Kimi K2.6 is 95% cheaper on input tokens than GPT-5.2 Pro. For output tokens, Kimi K2.6 is the more affordable option at $4.00/1M vs $168.00.
On context window, Kimi K2.6 supports 262,144 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-5.2 Pro
- ✓ You are already integrated with OpenAI
When to choose Kimi K2.6
- ✓ You need the lowest input token cost ($ 0.95/1M)
- ✓ Your workload is output-heavy — Kimi K2.6 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 GPT-5.2 Pro cheaper than Kimi K2.6? ▼
Kimi K2.6 is cheaper on input tokens at $0.95/1M vs $21.00/1M for GPT-5.2 Pro — a 95% saving.
What is the context window of GPT-5.2 Pro vs Kimi K2.6? ▼
GPT-5.2 Pro has a 128,000-token context window. Kimi K2.6 has a 262,144-token context window. Kimi K2.6 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-5.2 Pro or Kimi K2.6? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Kimi K2.6 is the cheaper option. For maximum context length, Kimi K2.6 supports 262,144 tokens. Use the comparison table above to find the right fit for your workload.