AI model
tencent/hy4-reasoning
Tencent: Hy4 (Reasoning) is a 1,048,576-token model served on Composite at $0.521 per million tokens in and $1.56 per million tokens out.
Try in Playground| Model ID | tencent/hy4-reasoning |
|---|---|
| Provider | cv11 |
| Context window | 1,048,576 tokens |
| Accepts | text, image |
| Returns | text |
| Input price | $0.521 per million tokens |
| Output price | $1.56 per million tokens |
| Prompt caching | Supported — cached input is billed at the provider's cache rate, on credits and plans alike |
| Thinking | Optional - see "Tencent: Hy4 (Reasoning) (Reasoning)" in the catalog to turn it on by default |
| Moderated | No |
| Cost on a monthly plan | About 4.6 plan credits per typical call (8k in, 1k out) |
| Routing endpoints | 1 |
Make a Composite API key and type tencent/hy4-reasoning 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.
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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.
$0.521 per million tokens input · $1.56 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 4.6 plan credits, at the provider's own price.
cv11
This model is available on Composite alongside dozens of others from other labs, so it is easy to compare against similar options.
With a 1,048,576-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.
It sits in the mid-range on price, a reasonable pick for regular roleplay use without going for the cheapest option available.
The official release of Hy4 delivers comprehensive and substantial improvements over Hy4 Preview, with particularly strong gains in agentic capabilities and performance across a wide range of long-horizon, real-world productivity...
Supplied by cv11, not written by Composite.
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