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Specifications
Specifications and pricing as served by Composite
Model ID
aion-labs/aion-rp-llama-3.1-8b
Provider
cv11
Context window
32,768 tokens
Accepts
text
Returns
text
Input price
$1.00 per million tokens
Output price
$2.00 per million tokens
Prompt caching
Not offered for this model
Moderated
No
Cost on a monthly plan
About 8.0 plan credits per typical call (8k in, 1k out)
Routing endpoints
2 (base plus 1 routing variant)
Use AionLabs: Aion-RP 1.0 (8B) in JanitorAI or SillyTavern
Make a Composite API key and type aion-labs/aion-rp-llama-3.1-8b as the model name. JanitorAI takes the full URL https://composite.lucidity.sh/v1/chat/completions; SillyTavern, ChubAI, Agnai and RisuAI take https://composite.lucidity.sh/v1. It runs on credits, a plan, or your own provider key.
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.
Route
Model ID
Provider
Price
cheapThink
aion-labs/aion-rp-llama-3.1-8b:cheapThink
cv11
$1.00 per million tokens input · $2.00 per million tokens output
Pricing
$1.00 per million tokens input · $2.00 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 8.0 plan credits, at the provider's own price.
Provider
cv11
Roleplay fit
Llama models are a widely-supported open baseline, useful when you want predictable, well-documented behavior.
Context behavior
Its 32,768-token context window covers most single-session roleplay threads comfortably. For campaigns that run over many sessions, expect older messages to eventually drop out of context.
Cost for regular use
It sits in the mid-range on price, a reasonable pick for regular roleplay use without going for the cheapest option available.
From the provider
Aion-RP-Llama-3.1-8B ranks the highest in the character evaluation portion of the RPBench-Auto benchmark, a roleplaying-specific variant of Arena-Hard-Auto, where LLMs evaluate each other’s responses. It is a fine-tuned base model...