Schematron V2 Turbo is $0.97 cheaper per 1M input tokens (97% lower; 33.3x difference).
API cost decision in 10 seconds
NewSchematron V2 Turbo vs GPT-5.6 Terra (batch)
Pick Schematron V2 Turbo for lower cost; pick GPT-5.6 Terra (batch) only if the larger context window matters more.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Schematron V2 Turbo for lower cost; pick GPT-5.6 Terra (batch) only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $4 for GPT-5.6 Terra (batch), saving $3.9 (97.4% lower).
Cost-first pickSchematron V2 Turbo
Context-first pickGPT-5.6 Terra (batch)
Sample savings$3.997.4%
10x traffic gap$38.95
GPT-5.6 Terra (batch) has more context, but Schematron V2 Turbo saves $3.9 on the standard workload. At 10x that traffic, the same price gap is about $38.95. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Schematron V2 Turbo stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Schematron V2 Turbo | GPT-5.6 Terra (batch) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Schematron V2 Turbo | $0.22 | $8 |
| Balanced workload | 1M input + 1M output | Schematron V2 Turbo | $0.18 | $7 |
| Output-heavy chatbot | 1M input + 5M output | Schematron V2 Turbo | $0.78 | $31 |
Schematron V2 Turbo is $5.85 cheaper per 1M output tokens (97.5% lower; 40x difference).
GPT-5.6 Terra (batch) has 922K more context (8.2x larger).
Schematron V2 Turbo is $3.9 cheaper on the standard workload (97.4% 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 Turbo has the lower input price; Schematron V2 Turbo has the lower output price; GPT-5.6 Terra (batch) offers the larger context window. For the 1M input plus 500K output sample, Schematron V2 Turbo is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.1 for Schematron V2 Turbo and $4 for GPT-5.6 Terra (batch).
Choose Schematron V2 Turbo when you care most about lower input-token price, and lower output-token price.
Choose GPT-5.6 Terra (batch) when you care most about larger context window.
- On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $4 for GPT-5.6 Terra (batch), saving $3.9 (97.4% lower).
- Schematron V2 Turbo is $3.9 cheaper on the standard workload (97.4% lower).
- Schematron V2 Turbo is $0.97 cheaper per 1M input tokens (97% lower; 33.3x difference).
- Schematron V2 Turbo is $5.85 cheaper per 1M output tokens (97.5% lower; 40x difference).
- GPT-5.6 Terra (batch) has 922K more context (8.2x larger).
| Feature | NewSchematron V2 Turbo (Inference.net) | GPT-5.6 Terra (batch) (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.03 | $1 |
| Completion Price per 1M tokens | $0.15 | $6 |
| Sample Workload Cost 1M input + 500K output | $0.1 | $4 |
| Context Window | 128K | 1.05M |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Schematron V2 Turbo | On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $4 for GPT-5.6 Terra (batch), saving $3.9 (97.4% lower). |
| High-volume input processing | Schematron V2 Turbo | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Schematron V2 Turbo | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5.6 Terra (batch) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- gpt-oss-120b (free) can replace GPT-5.6 Terra (batch) when lower sample workload cost matters most: $0.
- gpt-oss-20b (free) can replace GPT-5.6 Terra (batch) when lower sample workload cost matters most: $0.
- gpt-oss-20b can replace GPT-5.6 Terra (batch) when lower sample workload cost matters most: $0.1.
- gpt-oss-120b can replace GPT-5.6 Terra (batch) when lower sample workload cost matters most: $0.12.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- GLM 5.3 Flash offers 1.31M context with $0.4 sample workload cost.
- DeepSeek V4 Flash 0731 offers 1.31M context with $0.08 sample workload cost.
- Hy4 preview · Tencent · #1
- GPT-5.6 Luna · OpenAI · #2
- GLM 5.3 Flash · Z.ai · #3
- DeepSeek V4 Flash 0731 · DeepSeek · #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 hubsInference.net catalog
Review all tracked Inference.net models before deciding whether this matchup is the right shortlist.
Open Inference.net modelsOpenAI catalog
Check other OpenAI models with comparable pricing, context, or release timing.
Open OpenAI modelsSchematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must be supplied through a JSON schema in response_format rather...
GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic...