Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH is a 8 billion parameter chat model from Lixing-Li, released April 24, 2026. Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH is an open-weights chat model with roughly 8 billion parameters.
by Lixing-Li · 8B parameters
Best for
Ways to use Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Lixing-Li API key. osFoundry discovers Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH 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
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH 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 Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~20 GB).
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH
Is Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH free to use?
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH 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 Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH 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 Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH locally?
Yes. Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH best at?
Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH is well-suited to text generation.
How do I use Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH in osFoundry?
Paste your Lixing-Li API key in the key dialog (or deploy the open weights for self-hostable models), assign Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Lixing-Li on April 24, 2026. Source: https://huggingface.co/Lixing-Li/Llama-3.1-8B-LoRA-TENSORTRUST-LATE8TH