Kimi K2.5 is $0.2 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
API cost decision in 10 seconds
Kimi K2.5 vs Kimi K2 0905
Pick Kimi K2.5 when budget is the priority.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Kimi K2.5 when budget is the priority.
On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.85 for Kimi K2 0905, saving $0.5 (27% lower).
Cost-first pickKimi K2.5
Context-first pickBoth models
Sample savings$0.527%
10x traffic gap$5
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $5. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Kimi K2.5 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Kimi K2.5 | Kimi K2 0905 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Kimi K2.5 | $2.95 | $4.25 |
| Balanced workload | 1M input + 1M output | Kimi K2.5 | $2.3 | $3.1 |
| Output-heavy chatbot | 1M input + 5M output | Kimi K2.5 | $9.9 | $13.1 |
Kimi K2.5 is $0.6 cheaper per 1M output tokens (24% lower; 1.32x difference).
Both models report the same context window at 262.14K tokens.
Kimi K2.5 is $0.5 cheaper on the standard workload (27% 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 K2.5 has the lower input price; Kimi K2.5 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Kimi K2.5 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.35 for Kimi K2.5 and $1.85 for Kimi K2 0905.
Choose Kimi K2.5 when you care most about lower input-token price, and lower output-token price.
Choose Kimi K2 0905 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.85 for Kimi K2 0905, saving $0.5 (27% lower).
- Kimi K2.5 is $0.5 cheaper on the standard workload (27% lower).
- Kimi K2.5 is $0.2 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
- Kimi K2.5 is $0.6 cheaper per 1M output tokens (24% lower; 1.32x difference).
- Both models report the same context window at 262.14K tokens.
| Feature | Kimi K2.5 (MoonshotAI) | Kimi K2 0905 (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $0.6 |
| Completion Price per 1M tokens | $1.9 | $2.5 |
| Sample Workload Cost 1M input + 500K output | $1.35 | $1.85 |
| Context Window | 262.14K | 262.14K |
| Release Date | ||
| Popularity | #36 | #70 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Kimi K2.5 | On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.85 for Kimi K2 0905, saving $0.5 (27% lower). |
| High-volume input processing | Kimi K2.5 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Kimi K2.5 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Kimi K2 0711 can replace Kimi K2 0905 when lower sample workload cost matters most: $1.72.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
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Open provider hubsMoonshotAI catalog
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Open MoonshotAI modelsKimi 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...
Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32...