API cost decision in 10 seconds
Kimi K2.5 vs 🔥DeepSeek V3.2
Pick DeepSeek V3.2 for lower cost; pick Kimi K2.5 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 DeepSeek V3.2 for lower cost; pick Kimi K2.5 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $1.35 for Kimi K2.5, saving $0.91 (67.3% lower).
Cost-first pickDeepSeek V3.2
Context-first pickKimi K2.5
Sample savings$0.9167.3%
10x traffic gap$9.09
Kimi K2.5 has more context, but DeepSeek V3.2 saves $0.91 on the standard workload. At 10x that traffic, the same price gap is about $9.09. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
DeepSeek V3.2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Kimi K2.5 | DeepSeek V3.2 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | DeepSeek V3.2 | $2.95 | $1.45 |
| Balanced workload | 1M input + 1M output | DeepSeek V3.2 | $2.3 | $0.63 |
| Output-heavy chatbot | 1M input + 5M output | DeepSeek V3.2 | $9.9 | $2.14 |
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
DeepSeek V3.2 has the lower input price, DeepSeek V3.2 has the lower output price, and Kimi K2.5 offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.35 for Kimi K2.5 and $0.44 for DeepSeek V3.2.
Choose Kimi K2.5 when you care most about larger context window.
Choose DeepSeek V3.2 when you care most about lower input-token price, and lower output-token price.
| Feature | Kimi K2.5 (MoonshotAI) | 🔥DeepSeek V3.2 (DeepSeek) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $0.25 |
| Completion Price per 1M tokens | $1.9 | $0.38 |
| Sample Workload Cost 1M input + 500K output | $1.35 | $0.44 |
| Context Window | 262.14K | 131.07K |
| Release Date | 2026-01-27 | 2025-12-01 |
| Popularity | #8 |
Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | DeepSeek V3.2 | On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $1.35 for Kimi K2.5, saving $0.91 (67.3% lower). |
| High-volume input processing | DeepSeek V3.2 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | DeepSeek V3.2 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Kimi K2.5 | A larger context window leaves more room for retrieved passages and source files. |