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Inference.net: Schematron V2 Turbo

inference-net/schematron-v2-turbo

Inference.net: Schematron V2 Turbo is a 128,000-token model served on Composite at $0.0375 per million tokens in and $0.188 per million tokens out.

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Specifications

Specifications and pricing as served by Composite
Model IDinference-net/schematron-v2-turbo
Providercv11
Context window128,000 tokens
Acceptstext
Returnstext
Input price$0.0375 per million tokens
Output price$0.188 per million tokens
Prompt cachingSupported — cached input is billed at the provider's cache rate, on credits and plans alike
ModeratedNo
Cost on a monthly planAbout 0.4 plan credits per typical call (8k in, 1k out)
Routing endpoints2 (base plus 1 routing variant)

Measured on Composite

This model has not carried enough traffic on Composite yet to publish a success rate, a latency figure or a traffic rank. The numbers appear here once it has.

Routing variants

The same model behind 1 alternative endpoint. Call the id directly to pin a route; the base id above picks for you.

RouteModel IDProviderPrice
cheapThink inference-net/schematron-v2-turbo:cheapThink cv11 $0.0375 per million tokens input · $0.188 per million tokens output

Pricing

$0.0375 per million tokens input · $0.188 per million tokens output

Credits pay the provider’s price plus 25%; cache hits cost less.

On a monthly plan, a typical call (8k tokens in, 1k out) uses about 0.4 plan credits, at the provider's own price.

Provider

cv11

Roleplay fit

This model is available on Composite alongside dozens of others from other labs, so it is easy to compare against similar options.

Context behavior

With a 128,000-token context window, it can hold a long-running roleplay or a full lorebook in memory without losing earlier plot details, so it suits multi-session campaigns and character cards with heavy backstory.

Cost for regular use

It is priced low enough for high-volume daily roleplay without the per-message cost adding up quickly.

From the provider

Schematron 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...

Supplied by cv11, not written by Composite.