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Model details

Schematron V2 Small

Schematron V2 Small is a language model introduced through the Inference.net API on OpenRouter, appearing on the same day as a sibling Turbo variant. The model's listing positions it within Inference.net's Schematron V2 family, where the Small tier suggests a lighter configuration relative to its higher-end counterpart. the cataloged API limit context window is the most prominent contextual detail, indicating suitability for tasks that require processing long documents, extended dialogues, or sizable codebases within a single prompt. The simultaneous debut of both the Small and Turbo versions suggests Inference.net is offering the V2 line across multiple performance or cost tiers, allowing developers to choose between footprint and throughput depending on workload demands.

Practical deployment of Schematron V2 Small centers on its long-context capability, which supports use cases like document summarization, multi-file code analysis, and research synthesis where retaining extensive input is advantageous. As part of the Schematron V2 generation, it reflects Inference.net's forward step in making large-context models available across distinct size tiers, giving teams flexibility to balance responsiveness against resource consumption. The model's text-only nature and API-based availability through OpenRouter make it straightforward to integrate into existing pipelines, while its position alongside the Turbo variant implies a family designed to scale from lighter inference tasks to more demanding generation workloads.

OpenRouterinference-net/schematron-v2-small

Quick Info

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Provider
OpenRouter
Model key
inference-net/schematron-v2-small
Release date
Apr 16, 2026
Last updated
Apr 16, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.05
Output token cost
$0.23

Limits

Output tokens
8,192 tokens
Context window
128,000 tokens

Latest news about Schematron V2 Small

OpenRouter

Coverage

LLM Releases records Schematron V2 Small with 3B parameters and a 128K-token context window capped at 4K maximum output tokens. The catalog lists the model as proprietary with weights not released and architecture unknown, so developers cannot inspect or fine-tune the checkpoint themselves. That entry also shows text-only modalities, pricing of $0.05 per million input tokens and $0.23 per million output tokens, and no recorded benchmark scores, with vendor-reported figures treated as unverified claims. The absence of public benchmarks means comparative quality data for this variant rests on Inference.net's own testing.

OpenRouter

Coverage

ModelsAtlas catalogs inference-net/schematron-v2-small as a text-only LLM released on Sep 12, 2026, built for HTML-to-JSON extraction with a 128K context window. The entry notes that extraction instructions must be supplied through a JSON schema, and it lists supported sampling and structured-output parameters including structured outputs, response format, temperature, and top-p. The catalog record also carries API identifier inference-net/schematron-v2-small under provider Inference Net, with text input and output modalities and an unmoderated setup. Published pricing is listed at $0.05 per million input tokens and $0.23 per million output tokens, with no per-request or image fees, and the page was last refreshed on Oct 19, 2026.

OpenRouter

Coverage

Puter developer docs describe Schematron V2 Small, a 3-billion-parameter Inference.net model fine-tuned from Meta's Llama 3.2 3B that converts messy HTML into JSON matching a supplied schema. Unlike Turbo, Small is the quality-focused tier of the V2 lineup, taking the JSON schema and raw HTML as input so extraction instructions travel in the schema rather than in a system or user prompt. The same card reports that Schematron V2 Small handles about 2.47 requests per second on a single H100, scoring 4.060 out of 5 on Inference.net's extraction benchmark where both V2 tiers beat DeepSeek V3.2 and GPT-5.4 Nano. It lists a 128,000-token context window with a 4K-class output limit, plus catalog prices of $0.03 per million input tokens and $0.15 per million output tokens.

Sulat also reports on AI and tech beyond the catalog.Read news.sulat.com

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