CoLLMLight-8B-Llama3
CoLLMLight-8B-Llama3 is a 8 billion parameter chat model from ljxys, released May 12, 2026. CoLLMLight-8B-Llama3 is an open-weights chat model with roughly 8 billion parameters.
by ljxys · 8B parameters
Best for
Ways to use CoLLMLight-8B-Llama3 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your ljxys API key. osFoundry discovers CoLLMLight-8B-Llama3 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
CoLLMLight-8B-Llama3 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 CoLLMLight-8B-Llama3
CoLLMLight-8B-Llama3 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).
CoLLMLight-8B-Llama3 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about CoLLMLight-8B-Llama3
Is CoLLMLight-8B-Llama3 free to use?
CoLLMLight-8B-Llama3 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 CoLLMLight-8B-Llama3 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 CoLLMLight-8B-Llama3 need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run CoLLMLight-8B-Llama3 locally?
Yes. CoLLMLight-8B-Llama3 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is CoLLMLight-8B-Llama3 best at?
CoLLMLight-8B-Llama3 is well-suited to reinforcement learning.
How do I use CoLLMLight-8B-Llama3 in osFoundry?
Paste your ljxys API key in the key dialog (or deploy the open weights for self-hostable models), assign CoLLMLight-8B-Llama3 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by ljxys on May 12, 2026. Source: https://huggingface.co/ljxys/CoLLMLight-8B-Llama3