MiniMax M2.5 (free) is free for input tokens while DeepSeek V3.1 Nex N1 costs $0.14 per 1M tokens.
API cost decision in 10 seconds
MiniMax M2.5 (free) vs DeepSeek V3.1 Nex N1
Pick MiniMax M2.5 (free) when budget and context both matter.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick MiniMax M2.5 (free) when budget and context both matter.
On the standard 1M input plus 500K output workload, MiniMax M2.5 (free) is estimated at $0 vs $0.39 for DeepSeek V3.1 Nex N1, saving $0.39 (100% lower).
Cost-first pickMiniMax M2.5 (free)
Context-first pickMiniMax M2.5 (free)
Sample savings$0.39100%
10x traffic gap$3.85
MiniMax M2.5 (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $3.85. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
MiniMax M2.5 (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | MiniMax M2.5 (free) | DeepSeek V3.1 Nex N1 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2.5 (free) | $0 | $0.93 |
| Balanced workload | 1M input + 1M output | MiniMax M2.5 (free) | $0 | $0.64 |
| Output-heavy chatbot | 1M input + 5M output | MiniMax M2.5 (free) | $0 | $2.63 |
MiniMax M2.5 (free) is free for output tokens while DeepSeek V3.1 Nex N1 costs $0.5 per 1M tokens.
MiniMax M2.5 (free) has 73.73K more context (1.56x larger).
MiniMax M2.5 (free) is free for the standard workload while the other model is estimated at $0.39.
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 (free) has the lower input price; MiniMax M2.5 (free) has the lower output price; MiniMax M2.5 (free) offers the larger context window. For the 1M input plus 500K output sample, MiniMax M2.5 (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for MiniMax M2.5 (free) and $0.39 for DeepSeek V3.1 Nex N1.
Choose MiniMax M2.5 (free) when you care most about lower input-token price, lower output-token price, and larger context window.
Choose DeepSeek V3.1 Nex N1 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, MiniMax M2.5 (free) is estimated at $0 vs $0.39 for DeepSeek V3.1 Nex N1, saving $0.39 (100% lower).
- MiniMax M2.5 (free) is free for the standard workload while the other model is estimated at $0.39.
- MiniMax M2.5 (free) is free for input tokens while DeepSeek V3.1 Nex N1 costs $0.14 per 1M tokens.
- MiniMax M2.5 (free) is free for output tokens while DeepSeek V3.1 Nex N1 costs $0.5 per 1M tokens.
- MiniMax M2.5 (free) has 73.73K more context (1.56x larger).
| Feature | MiniMax M2.5 (free) (MiniMax) | DeepSeek V3.1 Nex N1 (Nex AGI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.135 |
| Completion Price per 1M tokens | $0 | $0.5 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.39 |
| Context Window | 204.8K | 131.07K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiniMax M2.5 (free) | On the standard 1M input plus 500K output workload, MiniMax M2.5 (free) is estimated at $0 vs $0.39 for DeepSeek V3.1 Nex N1, saving $0.39 (100% lower). |
| High-volume input processing | MiniMax M2.5 (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | MiniMax M2.5 (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | MiniMax M2.5 (free) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- No lower-cost same-provider swap is currently tracked for this pair.
- 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.
- DeepSeek V4 Flash (free) 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 hubsMiniMax catalog
Review all tracked MiniMax models before deciding whether this matchup is the right shortlist.
Open MiniMax modelsNex AGI catalog
Check other Nex AGI models with comparable pricing, context, or release timing.
Open Nex AGI 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...
DeepSeek V3.1 Nex-N1 is the flagship release of the Nex-N1 series — a post-trained model designed to highlight agent autonomy, tool use, and real-world productivity. Nex-N1 demonstrates competitive performance across...