MiMo-V2.5 is $0.85 cheaper per 1M input tokens (68% lower; 3.12x difference).
API cost decision in 10 seconds
MiMo-V2.5 vs Cogito v2.1 671B
Pick MiMo-V2.5 when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick MiMo-V2.5 when budget and context both matter.
On the standard 1M input plus 500K output workload, MiMo-V2.5 is estimated at $1.4 vs $1.88 for Cogito v2.1 671B, saving $0.48 (25.3% lower).
Cost-first pickMiMo-V2.5
Context-first pickMiMo-V2.5
Sample savings$0.4825.3%
10x traffic gap$4.75
MiMo-V2.5 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $4.75. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors MiMo-V2.5, balanced workload favors MiMo-V2.5, and output-heavy chatbot favors Cogito v2.1 671B.
| Workload shape | Token mix | Better pick | MiMo-V2.5 | Cogito v2.1 671B |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiMo-V2.5 | $3 | $6.88 |
| Balanced workload | 1M input + 1M output | MiMo-V2.5 | $2.4 | $2.5 |
| Output-heavy chatbot | 1M input + 5M output | Cogito v2.1 671B | $10.4 | $7.5 |
Cogito v2.1 671B is $0.75 cheaper per 1M output tokens (37.5% lower; 1.6x difference).
MiMo-V2.5 has 920.58K more context (8.19x larger).
MiMo-V2.5 is $0.48 cheaper on the standard workload (25.3% 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; Cogito v2.1 671B has the lower output price; MiMo-V2.5 offers the larger 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 $1.88 for Cogito v2.1 671B.
Choose MiMo-V2.5 when you care most about lower input-token price, and larger context window.
Choose Cogito v2.1 671B when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, MiMo-V2.5 is estimated at $1.4 vs $1.88 for Cogito v2.1 671B, saving $0.48 (25.3% lower).
- MiMo-V2.5 is $0.48 cheaper on the standard workload (25.3% lower).
- MiMo-V2.5 is $0.85 cheaper per 1M input tokens (68% lower; 3.12x difference).
- Cogito v2.1 671B is $0.75 cheaper per 1M output tokens (37.5% lower; 1.6x difference).
- MiMo-V2.5 has 920.58K more context (8.19x larger).
| Feature | MiMo-V2.5 (Xiaomi) | Cogito v2.1 671B (Deep Cogito) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $1.25 |
| Completion Price per 1M tokens | $2 | $1.25 |
| Sample Workload Cost 1M input + 500K output | $1.4 | $1.88 |
| Context Window | 1.05M | 128K |
| 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 $1.88 for Cogito v2.1 671B, saving $0.48 (25.3% 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 | Cogito v2.1 671B | 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
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