Schematron V2 Turbo with Jev
Schematron V2 Turbo is a model from Inference.net, released 2026-09-12. It costs $0.030 per million input tokens and $0.150 per million output tokens, reads up to 128K tokens of context, and writes up to 8,192 tokens in one reply. Through llm11, set model to inference-net/schematron-v2-turbo.
- Input price
- $0.030 / 1M
- Output price
- $0.150 / 1M
- Context window
- 128K tokens
- Max output
- 8K tokens
- Cached input
- $0.030 / 1M
- Released
- 2026-09-12
- Accepts
- text
Read from the provider's prompt cache
Read from the live catalogue and refreshed daily. At blended list price, 97% of the 332 priced models we can call cost more.
Using Schematron V2 Turbo with Jev
Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Schematron V2 Turbo does the answering when Jev sends it work, or when you name it yourself. At list price Schematron V2 Turbo falls in the llm11-fast band, but no pack routes to it because Inference.net is not one of the labs the packs draw from. You can still pin it: pass inference-net/schematron-v2-turbo as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for Schematron V2 Turbo with and without it, and this page does not invent any. Every response comes with a receipt that names the model that answered and what it cost against your most expensive model, so you can measure the pairing on your own traffic.
What a request costs
List price arithmetic, the same sum a receipt does. llm11 adds nothing per request; the only fee is on buying credits.
| Request | Tokens in / out | One | A thousand |
|---|---|---|---|
| Short chat turn | 500 / 200 | $0.00005 | $0.045 |
| Question over retrieved documents | 4,000 / 500 | $0.00019 | $0.195 |
| Long document summary | 30,000 / 1,000 | $0.00105 | $1.05 |
Cheaper models to try
The catalogue has no benchmark score for Schematron V2 Turbo, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Mistral Mistral Small 3 | $0.050 | $0.080 | 33K | |
| Meta Llama 3.1 8B Instruct | $0.050 | $0.080 | 131K | |
| Qwen Qwen3.7 Flash | $0.030 | $0.130 | 1M | |
| OpenAI gpt-oss-20b | $0.018 | $0.090 | 131K |
Call it
Same OpenAI request shape. Naming the model pins it, so nothing is routed, and the answer is still checked.
python
from openai import OpenAI
client = OpenAI(base_url="https://www.llm11.com/v1", api_key="llm11_live_...")
res = client.chat.completions.create(
model="inference-net/schematron-v2-turbo",
messages=[{"role": "user", "content": "Hello"}],
)More from Inference.net
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Schematron V2 Small | $0.050 | $0.230 | 128K |
Questions
- What is Schematron V2 Turbo with Jev?
- Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Schematron V2 Turbo does the answering when Jev sends it work, or when you name it yourself. At list price Schematron V2 Turbo falls in the llm11-fast band, but no pack routes to it because Inference.net is not one of the labs the packs draw from. You can still pin it: pass inference-net/schematron-v2-turbo as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Schematron V2 Turbo a System One model?
- No. Schematron V2 Turbo answers requests. The System One model is Jev, which decides which model answers each one, so the two do different jobs and llm11 uses both.
- How much does Schematron V2 Turbo cost?
- $0.030 per million input tokens and $0.150 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00019, so a thousand of them is about $0.195. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Schematron V2 Turbo context window?
- 128,000 tokens, with up to 8,192 tokens in a single reply.
- Does Schematron V2 Turbo support tool calling and structured output?
- The catalogue lists structured output, but it does not list tool calling and reasoning controls.
- Can I use Schematron V2 Turbo through llm11?
- Yes. Set model to inference-net/schematron-v2-turbo on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Schematron V2 Turbo?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price Schematron V2 Turbo falls in the llm11-fast band, but no pack routes to it because Inference.net is not one of the labs the packs draw from. You can still pin it: pass inference-net/schematron-v2-turbo as model and routing steps aside while verification still runs.
- What is a cheaper alternative to Schematron V2 Turbo?
- Nearest in price and below it: Mistral Mistral Small 3 at $0.050 in and $0.080 out, Meta Llama 3.1 8B Instruct at $0.050 in and $0.080 out and Qwen Qwen3.7 Flash at $0.030 in and $0.130 out. The catalogue has no benchmark score for Schematron V2 Turbo, so this is a price ordering. It does not claim these answer as well.