Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound
Released by Intel in 2026, Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound is a 122 billion parameter chat model. Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound is an open-weights chat model with roughly 122 billion parameters.
by Intel · 122B parameters
Best for
- complex multi-step reasoning
- agent orchestration with tool use
- long-document analysis and summarisation
Ways to use Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Intel API key. osFoundry discovers Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound 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
Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound 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 Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound
Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound runs on a single A100 80GB or H100 80GB at Q4 quantisation (~74 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~293 GB).
Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound
Is Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound free to use?
Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound 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 Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound 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 Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound need?
Approximately 74 GB at Q4 quantisation, or 293 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound locally?
Yes. Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound best at?
Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound is well-suited to complex multi-step reasoning, agent orchestration with tool use, long-document analysis and summarisation.
How do I use Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound in osFoundry?
Paste your Intel API key in the key dialog (or deploy the open weights for self-hostable models), assign Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Intel on March 23, 2026. Source: https://huggingface.co/Intel/Qwen3.5-122B-A10B-gguf-q2ks-mixed-AutoRound