Inference.net: Schematron V2 Small

inference-net/schematron-v2-small

Access Schematron V2 Small from Inference.net using the Puter.js AI API.

Get Started

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "inference-net/schematron-v2-small"
}).then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "inference-net/schematron-v2-small"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

Model Card

Schematron V2 Small is a 3-billion-parameter HTML-to-JSON extraction model from Inference.net, fine-tuned from Meta's Llama 3.2 3B.

It takes a JSON schema and raw HTML as input and returns schema-conformant structured output; extraction instructions go through the schema itself rather than a system or user prompt. Inference.net built it as the quality-focused tier of its V2 lineup, approaching 8B-level accuracy at roughly 3B-level speed, alongside a faster Turbo variant.

On Inference.net's internal LLM-as-judge benchmark it scores 4.06 out of 5, close to the original Schematron 8B's 4.07 and ahead of the first-generation 3B's 3.91. On SimpleQA it scores 83.1, and Inference.net reports both V2 models beating DeepSeek V3.2 and GPT-5.4 Nano on that benchmark despite being much smaller.

It targets web scraping, product data ingestion, financial document parsing, and search-augmented pipelines needing reliable structured output over long pages, with a 128K context window and 4,096-token output limit.

Context Window 128K

tokens

Max Output 4K

tokens

Input Cost $0.05

per million tokens

Output Cost $0.23

per million tokens

Release Date Sep 12, 2026

Model Playground

Try Schematron V2 Small instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat inference-net/schematron-v2-small

Chat with Schematron V2 Small

More AI Models From Inference.net

Find other Inference.net models →

Chat

Schematron V2 Turbo

Schematron V2 Turbo is a 3-billion-parameter model from Inference.net built to turn messy HTML into JSON matching a schema you supply, using schema-constrained decoding so the output is valid JSON by construction rather than by retry. It's the throughput-optimized sibling to Schematron V2 Small, handling 4.14 requests per second on a single H100 versus Small's 2.47, a 2.5x gain over the original Schematron 3B. It shares Small's 128,000-token context but doubles its output limit, to 8,192 tokens. On Inference.net's quality benchmark it scores 4.039 out of 5, close to Small's 4.060, and both beat DeepSeek V3.2 and GPT-5.4 Nano on extraction accuracy. On SimpleQA, a web-search factuality benchmark, it reaches 79.42 against Small's 83.10. It suits web scraping and data extraction pipelines that prioritize speed and cost; the endpoint doesn't support tool calling.

Frequently Asked Questions

How do I use Schematron V2 Small?

You can access Schematron V2 Small by Inference.net through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Schematron V2 Small free?

Schematron V2 Small is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.

What is the pricing for Schematron V2 Small?

Schematron V2 Small costs $0.05 per 1M input tokens and $0.23 per 1M output tokens.

	Price per 1M tokens
Input	$0.05
Output	$0.23

Who created Schematron V2 Small?

Schematron V2 Small was created by Inference.net and released on Sep 12, 2026.

What is the context window of Schematron V2 Small?

Schematron V2 Small supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.

What is the max output length of Schematron V2 Small?

Schematron V2 Small can generate up to 4K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Schematron V2 Small API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Add Schematron V2 Small to your app for free

Developers can integrate Schematron V2 Small for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.

Get started How pricing works