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Specifications
Specifications and pricing as served by Composite
Model ID
tencent/hunyuan-a13b-instruct
Provider
cv11
Context window
131,072 tokens
Accepts
text
Returns
text
Input price
$0.175 per million tokens
Output price
$0.713 per million tokens
Prompt caching
Not offered for this model
Moderated
No
Cost on a monthly plan
About 1.7 plan credits per typical call (8k in, 1k out)
Routing endpoints
2 (base plus 1 routing variant)
Use Tencent: Hunyuan A13B Instruct in JanitorAI or SillyTavern
Make a Composite API key and type tencent/hunyuan-a13b-instruct 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
tencent/hunyuan-a13b-instruct:cheapThink
cv11
$0.175 per million tokens input · $0.713 per million tokens output
Pricing
$0.175 per million tokens input · $0.713 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 1.7 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 131,072-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
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...