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Катерина Кобзаренко

10.07.2026

Setup Qwen3-VL-235B-A22B-Instruct Using Pinokio with 1M Context

VectorDB | 0 коментарів

Setup Qwen3-VL-235B-A22B-Instruct Using Pinokio with 1M Context

A standalone PowerShell module provides the fastest route to local installation.

Use the instructions provided below to complete the setup.

The setup auto-streams the model assets (expect a multi-GB download).

You don’t need to tweak anything; the installer picks the highest performing setup.

🔐 Hash sum: f63f33a4ed3cf42aeaa9d7f22077a00e | 📅 Last update: 2026-07-04



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Qwen3-VL-235B-A22B-Instruct model combines a massive 235 billion parameters with an A22B architecture to deliver state‑of‑the‑art multimodal understanding. It processes text and images simultaneously, enabling high‑fidelity vision‑language tasks such as caption generation, visual question answering, and diagram interpretation. The model was fine‑tuned on a diverse corpus of web‑scale text and image‑caption pairs, which improves its contextual reasoning and visual grounding. Its context window extends to 32 k tokens, allowing it to retain long‑range dependencies across documents and complex scenes. In benchmark evaluations, Qwen3-VL-235B-A22B-Instruct consistently outperforms prior large multimodal models on both accuracy and efficiency metrics. The accompanying instruction‑tuned variant ensures reliable performance on user‑centric prompts, making it suitable for production‑grade AI assistants.

Metric Value
Parameters 235 B
Context Length 32 k tokens
Modalities Text + Image
Training Data Web‑scale text & image‑caption pairs
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