API cost decision in 10 seconds
MiMo-V2.5 vs MiniMax M2
Pick MiniMax M2 for lower cost; pick MiMo-V2.5 only if the larger context window matters more.
Budget verdict
Pick MiniMax M2 for lower cost; pick MiMo-V2.5 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, MiniMax M2 is estimated at $0.76 vs $1.4 for MiMo-V2.5, saving $0.64 (46.1% lower).
MiMo-V2.5 has more context, but MiniMax M2 saves $0.64 on the standard workload. At 10x that traffic, the same price gap is about $6.45. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
MiniMax M2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | MiMo-V2.5 | MiniMax M2 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2 | $3 | $1.77 |
| Balanced workload | 1M input + 1M output | MiniMax M2 | $2.4 | $1.25 |
| Output-heavy chatbot | 1M input + 5M output | MiniMax M2 | $10.4 | $5.25 |
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
MiniMax M2 has the lower input price, MiniMax M2 has the lower output price, and MiMo-V2.5 offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.4 for MiMo-V2.5 and $0.76 for MiniMax M2.
Choose MiMo-V2.5 when you care most about larger context window.
Choose MiniMax M2 when you care most about lower input-token price, and lower output-token price.
| Feature | MiMo-V2.5 (Xiaomi) | MiniMax M2 (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $0.26 |
| Completion Price per 1M tokens | $2 | $1 |
| Sample Workload Cost 1M input + 500K output | $1.4 | $0.76 |
| Context Window | 1.05M | 204.8K |
| Release Date | 2026-04-22 | 2025-10-23 |
MiMo-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...
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiniMax M2 | On the standard 1M input plus 500K output workload, MiniMax M2 is estimated at $0.76 vs $1.4 for MiMo-V2.5, saving $0.64 (46.1% lower). |
| High-volume input processing | MiniMax M2 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | MiniMax M2 | 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 and source files. |