MiniMax M2.5 is $0.05 cheaper per 1M input tokens (25% lower; 1.33x difference).
API cost decision in 10 seconds
MiniMax M2.5 vs NewStep 3.7 Flash
Pick MiniMax M2.5 for lower cost; pick Step 3.7 Flash only if the larger context window matters more.
Budget verdict
Pick MiniMax M2.5 for lower cost; pick Step 3.7 Flash only if the larger context window matters more.
On the standard 1M input plus 500K output workload, MiniMax M2.5 is estimated at $0.72 vs $0.77 for Step 3.7 Flash, saving $0.05 (6.5% lower).
Step 3.7 Flash has more context, but MiniMax M2.5 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
MiniMax M2.5 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | MiniMax M2.5 | Step 3.7 Flash |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2.5 | $1.32 | $1.57 |
| Balanced workload | 1M input + 1M output | MiniMax M2.5 | $1.3 | $1.35 |
| Output-heavy chatbot | 1M input + 5M output | MiniMax M2.5 | $5.9 | $5.95 |
Both models report the same output price at $1.15 per 1M tokens.
Step 3.7 Flash has 51.2K more context (1.25x larger).
MiniMax M2.5 is $0.05 cheaper on the standard workload (6.5% 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
MiniMax M2.5 has the lower input price; both models tie on output price; Step 3.7 Flash offers the larger context window. For the 1M input plus 500K output sample, MiniMax M2.5 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.72 for MiniMax M2.5 and $0.77 for Step 3.7 Flash.
Choose MiniMax M2.5 when you care most about lower input-token price.
Choose Step 3.7 Flash when you care most about larger context window.
- On the standard 1M input plus 500K output workload, MiniMax M2.5 is estimated at $0.72 vs $0.77 for Step 3.7 Flash, saving $0.05 (6.5% lower).
- MiniMax M2.5 is $0.05 cheaper on the standard workload (6.5% lower).
- MiniMax M2.5 is $0.05 cheaper per 1M input tokens (25% lower; 1.33x difference).
- Both models report the same output price at $1.15 per 1M tokens.
- Step 3.7 Flash has 51.2K more context (1.25x larger).
| Feature | MiniMax M2.5 (MiniMax) | NewStep 3.7 Flash (StepFun) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.15 | $0.2 |
| Completion Price per 1M tokens | $1.15 | $1.15 |
| Sample Workload Cost 1M input + 500K output | $0.72 | $0.77 |
| Context Window | 204.8K | 256K |
| Release Date | ||
| Popularity | #34 | #101 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiniMax M2.5 | On the standard 1M input plus 500K output workload, MiniMax M2.5 is estimated at $0.72 vs $0.77 for Step 3.7 Flash, saving $0.05 (6.5% lower). |
| High-volume input processing | MiniMax M2.5 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Tie | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Step 3.7 Flash | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- MiniMax M2.5 (free) can replace MiniMax M2.5 when lower sample workload cost matters most: $0.
- Step 3.5 Flash can replace Step 3.7 Flash when lower sample workload cost matters most: $0.24.
- 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.
- MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
- Hy3 preview · Tencent · #1
- DeepSeek V4 Flash · DeepSeek · #2
- MiMo-V2.5 · Xiaomi · #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
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Open provider hubsMiniMax catalog
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Open MiniMax modelsStepFun catalog
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Open StepFun modelsMiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...
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