Xinyuan-LLM-14B-0428
Xinyuan-LLM-14B-0428 is a 14 billion parameter chat model from Cylingo, released April 29, 2025. Xinyuan-LLM-14B-0428 is an open-weights chat model with roughly 14 billion parameters.
by Cylingo · 14B parameters
Best for
Ways to use Xinyuan-LLM-14B-0428 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Cylingo API key. osFoundry discovers Xinyuan-LLM-14B-0428 automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Xinyuan-LLM-14B-0428 is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run Xinyuan-LLM-14B-0428
Xinyuan-LLM-14B-0428 runs on a single 16GB consumer GPU (~9 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~34 GB).
Xinyuan-LLM-14B-0428 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Xinyuan-LLM-14B-0428
Is Xinyuan-LLM-14B-0428 free to use?
Xinyuan-LLM-14B-0428 is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Xinyuan-LLM-14B-0428 commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Xinyuan-LLM-14B-0428 need?
Approximately 9 GB at Q4 quantisation, or 34 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Xinyuan-LLM-14B-0428 locally?
Yes. Xinyuan-LLM-14B-0428 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Xinyuan-LLM-14B-0428 best at?
Xinyuan-LLM-14B-0428 is well-suited to text generation.
How do I use Xinyuan-LLM-14B-0428 in osFoundry?
Paste your Cylingo API key in the key dialog (or deploy the open weights for self-hostable models), assign Xinyuan-LLM-14B-0428 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Cylingo on April 29, 2025. Source: https://huggingface.co/Cylingo/Xinyuan-LLM-14B-0428