Schematron V2 Small is $0.02 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
API cost decision in 10 seconds
NewLing 3.1 Flash vs Schematron V2 Small
Pick Schematron V2 Small for lower cost; pick Ling 3.1 Flash only if the larger context window matters more.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Schematron V2 Small for lower cost; pick Ling 3.1 Flash only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Schematron V2 Small is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.02 (12% lower).
Cost-first pickSchematron V2 Small
Context-first pickLing 3.1 Flash
Sample savings$0.0212%
10x traffic gap$0.22
Ling 3.1 Flash has more context, but Schematron V2 Small saves $0.02 on the standard workload. At 10x that traffic, the same price gap is about $0.22. 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 Schematron V2 Small, balanced workload favors Schematron V2 Small, and output-heavy chatbot favors Tie.
| Workload shape | Token mix | Better pick | Ling 3.1 Flash | Schematron V2 Small |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Schematron V2 Small | $0.49 | $0.36 |
| Balanced workload | 1M input + 1M output | Schematron V2 Small | $0.3 | $0.28 |
| Output-heavy chatbot | 1M input + 5M output | Tie | $1.2 | $1.2 |
Ling 3.1 Flash is $0.005 cheaper per 1M output tokens (2.2% lower; 1.02x difference).
Ling 3.1 Flash has 134.14K more context (2.05x larger).
Schematron V2 Small is $0.02 cheaper on the standard workload (12% 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
Schematron V2 Small has the lower input price; Ling 3.1 Flash has the lower output price; Ling 3.1 Flash offers the larger context window. For the 1M input plus 500K output sample, Schematron V2 Small is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.19 for Ling 3.1 Flash and $0.17 for Schematron V2 Small.
Choose Ling 3.1 Flash when you care most about lower output-token price, and larger context window.
Choose Schematron V2 Small when you care most about lower input-token price.
- On the standard 1M input plus 500K output workload, Schematron V2 Small is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.02 (12% lower).
- Schematron V2 Small is $0.02 cheaper on the standard workload (12% lower).
- Schematron V2 Small is $0.02 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
- Ling 3.1 Flash is $0.005 cheaper per 1M output tokens (2.2% lower; 1.02x difference).
- Ling 3.1 Flash has 134.14K more context (2.05x larger).
| Feature | NewLing 3.1 Flash (inclusionAI) | Schematron V2 Small (Inference.net) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.075 | $0.05 |
| Completion Price per 1M tokens | $0.225 | $0.23 |
| Sample Workload Cost 1M input + 500K output | $0.19 | $0.17 |
| Context Window | 262.14K | 128K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Schematron V2 Small | On the standard 1M input plus 500K output workload, Schematron V2 Small is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.02 (12% lower). |
| High-volume input processing | Schematron V2 Small | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling 3.1 Flash | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Ling 3.1 Flash | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Ling 3.0 Flash VL (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Flash Sante (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Flash Fin (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Tiny (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- GPT-6 Luna Pro (batch) offers 1.05M context with $0.17 sample workload cost.
- GPT-6 Luna (batch) offers 1.05M context with $0.17 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- Muse Spark 1.3 Contributor offers 1.05M context with $0.2 sample workload cost.
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- Step 5 Preview · StepFun · #2
- GLM 5.3 Flash · Z.ai · #3
- MiMo-V2.6-Flash · Xiaomi · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
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Open provider hubsinclusionAI catalog
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Open inclusionAI modelsInference.net catalog
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Open Inference.net modelsLing 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total.
Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instructions must be supplied through a JSON schema...