MiMo-V2.5 is $0.6 cheaper per 1M input tokens (60% lower; 2.5x difference).
API cost decision in 10 seconds
MiMo-V2.5 vs MiMo-V2-Pro
Pick MiMo-V2.5 when budget is the priority.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick MiMo-V2.5 when budget is the priority.
On the standard 1M input plus 500K output workload, MiMo-V2.5 is estimated at $1.4 vs $2.5 for MiMo-V2-Pro, saving $1.1 (44% lower).
Cost-first pickMiMo-V2.5
Context-first pickBoth models
Sample savings$1.144%
10x traffic gap$11
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $11. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
MiMo-V2.5 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | MiMo-V2.5 | MiMo-V2-Pro |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiMo-V2.5 | $3 | $6.5 |
| Balanced workload | 1M input + 1M output | MiMo-V2.5 | $2.4 | $4 |
| Output-heavy chatbot | 1M input + 5M output | MiMo-V2.5 | $10.4 | $16 |
MiMo-V2.5 is $1 cheaper per 1M output tokens (33.3% lower; 1.5x difference).
Both models report the same context window at 1.05M tokens.
MiMo-V2.5 is $1.1 cheaper on the standard workload (44% 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
MiMo-V2.5 has the lower input price; MiMo-V2.5 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, MiMo-V2.5 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 $2.5 for MiMo-V2-Pro.
Choose MiMo-V2.5 when you care most about lower input-token price, and lower output-token price.
Choose MiMo-V2-Pro 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, MiMo-V2.5 is estimated at $1.4 vs $2.5 for MiMo-V2-Pro, saving $1.1 (44% lower).
- MiMo-V2.5 is $1.1 cheaper on the standard workload (44% lower).
- MiMo-V2.5 is $0.6 cheaper per 1M input tokens (60% lower; 2.5x difference).
- MiMo-V2.5 is $1 cheaper per 1M output tokens (33.3% lower; 1.5x difference).
- Both models report the same context window at 1.05M tokens.
| Feature | MiMo-V2.5 (Xiaomi) | MiMo-V2-Pro (Xiaomi) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $1 |
| Completion Price per 1M tokens | $2 | $3 |
| Sample Workload Cost 1M input + 500K output | $1.4 | $2.5 |
| Context Window | 1.05M | 1.05M |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiMo-V2.5 | On the standard 1M input plus 500K output workload, MiMo-V2.5 is estimated at $1.4 vs $2.5 for MiMo-V2-Pro, saving $1.1 (44% lower). |
| High-volume input processing | MiMo-V2.5 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | MiMo-V2.5 | 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
- MiMo-V2-Flash can replace MiMo-V2.5 when lower sample workload cost matters most: $0.25.
- MiMo-V2-Omni can replace MiMo-V2-Pro when lower sample workload cost matters most: $1.4.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- No popular competitor is currently available.
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 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...
MiMo-V2-Pro is Xiaomi's flagship foundation model, featuring over 1T total parameters and a 1M context length, deeply optimized for agentic scenarios. It is highly adaptable to general agent frameworks like...