Kimi K2 Thinking is $1.15 cheaper per 1M input tokens (65.7% lower; 2.92x difference).
API cost decision in 10 seconds
GPT-5.2-Codex vs Kimi K2 Thinking
Pick Kimi K2 Thinking for lower cost; pick GPT-5.2-Codex only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Kimi K2 Thinking for lower cost; pick GPT-5.2-Codex only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Kimi K2 Thinking is estimated at $1.85 vs $8.75 for GPT-5.2-Codex, saving $6.9 (78.9% lower).
Cost-first pickKimi K2 Thinking
Context-first pickGPT-5.2-Codex
Sample savings$6.978.9%
10x traffic gap$69
GPT-5.2-Codex has more context, but Kimi K2 Thinking saves $6.9 on the standard workload. At 10x that traffic, the same price gap is about $69. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Kimi K2 Thinking stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GPT-5.2-Codex | Kimi K2 Thinking |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Kimi K2 Thinking | $15.75 | $4.25 |
| Balanced workload | 1M input + 1M output | Kimi K2 Thinking | $15.75 | $3.1 |
| Output-heavy chatbot | 1M input + 5M output | Kimi K2 Thinking | $71.75 | $13.1 |
Kimi K2 Thinking is $11.5 cheaper per 1M output tokens (82.1% lower; 5.6x difference).
GPT-5.2-Codex has 137.86K more context (1.53x larger).
Kimi K2 Thinking is $6.9 cheaper on the standard workload (78.9% lower).
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Kimi K2 Thinking has the lower input price; Kimi K2 Thinking has the lower output price; GPT-5.2-Codex offers the larger context window. For the 1M input plus 500K output sample, Kimi K2 Thinking is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $8.75 for GPT-5.2-Codex and $1.85 for Kimi K2 Thinking.
Choose GPT-5.2-Codex when you care most about larger context window.
Choose Kimi K2 Thinking when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Kimi K2 Thinking is estimated at $1.85 vs $8.75 for GPT-5.2-Codex, saving $6.9 (78.9% lower).
- Kimi K2 Thinking is $6.9 cheaper on the standard workload (78.9% lower).
- Kimi K2 Thinking is $1.15 cheaper per 1M input tokens (65.7% lower; 2.92x difference).
- Kimi K2 Thinking is $11.5 cheaper per 1M output tokens (82.1% lower; 5.6x difference).
- GPT-5.2-Codex has 137.86K more context (1.53x larger).
| Feature | GPT-5.2-Codex (OpenAI) | Kimi K2 Thinking (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $1.75 | $0.6 |
| Completion Price per 1M tokens | $14 | $2.5 |
| Sample Workload Cost 1M input + 500K output | $8.75 | $1.85 |
| Context Window | 400K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Kimi K2 Thinking | On the standard 1M input plus 500K output workload, Kimi K2 Thinking is estimated at $1.85 vs $8.75 for GPT-5.2-Codex, saving $6.9 (78.9% lower). |
| High-volume input processing | Kimi K2 Thinking | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Kimi K2 Thinking | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5.2-Codex | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- gpt-oss-120b (free) can replace GPT-5.2-Codex when lower sample workload cost matters most: $0.
- gpt-oss-20b (free) can replace GPT-5.2-Codex when lower sample workload cost matters most: $0.
- gpt-oss-20b can replace GPT-5.2-Codex when lower sample workload cost matters most: $0.1.
- gpt-oss-120b can replace GPT-5.2-Codex when lower sample workload cost matters most: $0.13.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Grok 4.20 Multi-Agent offers 2M context with $5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- GPT-5.4 offers 1.05M context with $10 sample workload cost.
- No popular competitor is currently available.
Cheaper alternatives
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