InternVL2_5-1B-GGUF-BPU
D-Robotics's InternVL2_5-1B-GGUF-BPU packs 1 billion parameters into a image-generation model. InternVL2_5-1B-GGUF-BPU is an open-weights image model with roughly 1 billion parameters.
by D-Robotics · 1B parameters
Best for
Ways to use InternVL2_5-1B-GGUF-BPU in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your D-Robotics API key. osFoundry discovers InternVL2_5-1B-GGUF-BPU 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
InternVL2_5-1B-GGUF-BPU 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 InternVL2_5-1B-GGUF-BPU
InternVL2_5-1B-GGUF-BPU runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
InternVL2_5-1B-GGUF-BPU vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about InternVL2_5-1B-GGUF-BPU
Is InternVL2_5-1B-GGUF-BPU free to use?
InternVL2_5-1B-GGUF-BPU 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 InternVL2_5-1B-GGUF-BPU 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 InternVL2_5-1B-GGUF-BPU need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run InternVL2_5-1B-GGUF-BPU locally?
Yes. InternVL2_5-1B-GGUF-BPU is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is InternVL2_5-1B-GGUF-BPU best at?
InternVL2_5-1B-GGUF-BPU is well-suited to image text to text.
How do I use InternVL2_5-1B-GGUF-BPU in osFoundry?
Paste your D-Robotics API key in the key dialog (or deploy the open weights for self-hostable models), assign InternVL2_5-1B-GGUF-BPU to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by D-Robotics on February 21, 2025. Source: https://huggingface.co/D-Robotics/InternVL2_5-1B-GGUF-BPU