Ling-3.0-flash (free) is free for input tokens while Nex-N2-Pro costs $0.25 per 1M tokens.
API cost decision in 10 seconds
Ling-3.0-flash (free) vs Nex-N2-Pro
Pick Ling-3.0-flash (free) when budget is the priority.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Ling-3.0-flash (free) when budget is the priority.
On the standard 1M input plus 500K output workload, Ling-3.0-flash (free) is estimated at $0 vs $0.75 for Nex-N2-Pro, saving $0.75 (100% lower).
Cost-first pickLing-3.0-flash (free)
Context-first pickBoth models
Sample savings$0.75100%
10x traffic gap$7.5
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $7.5. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Ling-3.0-flash (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Ling-3.0-flash (free) | Nex-N2-Pro |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Ling-3.0-flash (free) | $0 | $1.75 |
| Balanced workload | 1M input + 1M output | Ling-3.0-flash (free) | $0 | $1.25 |
| Output-heavy chatbot | 1M input + 5M output | Ling-3.0-flash (free) | $0 | $5.25 |
Ling-3.0-flash (free) is free for output tokens while Nex-N2-Pro costs $1 per 1M tokens.
Both models report the same context window at 262.14K tokens.
Ling-3.0-flash (free) is free for the standard workload while the other model is estimated at $0.75.
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
Ling-3.0-flash (free) has the lower input price; Ling-3.0-flash (free) has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Ling-3.0-flash (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Ling-3.0-flash (free) and $0.75 for Nex-N2-Pro.
Choose Ling-3.0-flash (free) when you care most about lower input-token price, and lower output-token price.
Choose Nex-N2-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, Ling-3.0-flash (free) is estimated at $0 vs $0.75 for Nex-N2-Pro, saving $0.75 (100% lower).
- Ling-3.0-flash (free) is free for the standard workload while the other model is estimated at $0.75.
- Ling-3.0-flash (free) is free for input tokens while Nex-N2-Pro costs $0.25 per 1M tokens.
- Ling-3.0-flash (free) is free for output tokens while Nex-N2-Pro costs $1 per 1M tokens.
- Both models report the same context window at 262.14K tokens.
| Feature | Ling-3.0-flash (free) (inclusionAI) | Nex-N2-Pro (Nex AGI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.25 |
| Completion Price per 1M tokens | $0 | $1 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.75 |
| Context Window | 262.14K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Ling-3.0-flash (free) | On the standard 1M input plus 500K output workload, Ling-3.0-flash (free) is estimated at $0 vs $0.75 for Nex-N2-Pro, saving $0.75 (100% lower). |
| High-volume input processing | Ling-3.0-flash (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling-3.0-flash (free) | 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
- Nex-N2-Pro (free) can replace Nex-N2-Pro when lower sample workload cost matters most: $0.
- Nex-N2-Mini can replace Nex-N2-Pro when lower sample workload cost matters most: $0.08.
- DeepSeek V3.1 Nex N1 can replace Nex-N2-Pro when lower sample workload cost matters most: $0.39.
- DeepSeek V4 Flash 0731 offers 1.31M context with $0.17 sample workload cost.
- DeepSeek V4 Flash Latest offers 1.31M context with $0.11 sample workload cost.
- Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
- MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
- DeepSeek V4 Flash 0731 · DeepSeek · #1
- MiMo-V2.5 · Xiaomi · #2
- Hy3 · Tencent · #3
- Ox Alpha · stealth · #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
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsinclusionAI catalog
Review all tracked inclusionAI models before deciding whether this matchup is the right shortlist.
Open inclusionAI modelsNex AGI catalog
Check other Nex AGI models with comparable pricing, context, or release timing.
Open Nex AGI models*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...
Nex-N2-Pro is an agentic mixture-of-experts model from Nex AGI, with 17B active parameters out of 397B total. Built on the Qwen3.5 architecture, it accepts text and image input and produces...