Both models report the same input price at $0.4 per 1M tokens.
API cost decision in 10 seconds
MiMo-V2.5 vs Kimi K2.5
Pick Kimi K2.5 for lower cost; pick MiMo-V2.5 only if the larger context window matters more.
Budget verdict
Pick Kimi K2.5 for lower cost; pick MiMo-V2.5 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.4 for MiMo-V2.5, saving $0.05 (3.6% lower).
MiMo-V2.5 has more context, but Kimi K2.5 saves $0.05 on the standard workload. At 10x that traffic, the same price gap is about $0.5. 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 | MiMo-V2.5 | Kimi K2.5 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Kimi K2.5 | $3 | $2.95 |
| Balanced workload | 1M input + 1M output | Kimi K2.5 | $2.4 | $2.3 |
| Output-heavy chatbot | 1M input + 5M output | Kimi K2.5 | $10.4 | $9.9 |
Kimi K2.5 is $0.1 cheaper per 1M output tokens (5% lower; 1.05x difference).
MiMo-V2.5 has 786.43K more context (4x larger).
Kimi K2.5 is $0.05 cheaper on the standard workload (3.6% 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
both models tie on input price; Kimi K2.5 has the lower output price; MiMo-V2.5 offers the larger 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 $1.4 for MiMo-V2.5 and $1.35 for Kimi K2.5.
Choose MiMo-V2.5 when you care most about larger context window.
Choose Kimi K2.5 when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.4 for MiMo-V2.5, saving $0.05 (3.6% lower).
- Kimi K2.5 is $0.05 cheaper on the standard workload (3.6% lower).
- Both models report the same input price at $0.4 per 1M tokens.
- Kimi K2.5 is $0.1 cheaper per 1M output tokens (5% lower; 1.05x difference).
- MiMo-V2.5 has 786.43K more context (4x larger).
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 $1.4 for MiMo-V2.5, saving $0.05 (3.6% lower). |
| High-volume input processing | Tie | 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 | MiMo-V2.5 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- MiMo-V2-Flash can replace MiMo-V2.5 when lower sample workload cost matters most: $0.25.
- 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 · 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.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsXiaomi catalog
Review all tracked Xiaomi models before deciding whether this matchup is the right shortlist.
Open Xiaomi modelsMoonshotAI catalog
Check other MoonshotAI models with comparable pricing, context, or release timing.
Open MoonshotAI modelsMiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...
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...