Qwen 3 VL 30B-A3B

Overview

Qwen 3 VL's sweet spot: a 30B MoE with 3B active parameters and 256k context. Delivers most of the 235B's quality at a fraction of the hardware cost.

When to pick this model

• Single-GPU multimodal deployments
• Long-context document and chart analysis
• Cost-conscious teams wanting near-flagship vision
• Apache-licensed VLM for commercial products

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	19 GB
Q5_K_M	23 GB
Q8_0	35 GB
FP16 (no quantization)	62 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• Around 19 GB VRAM at Q4 — fits a single 24 GB card
• Native 262k multimodal context
• Efficient MoE with only 3B active parameters
• Apache 2.0

Limitations

• Lags the 235B on complex scene understanding
• Fewer fine-tunes than the older Qwen2-VL family

Architecture & training

Architecture: MoE vision · 30B · Qwen3-VL · 262k context

Training: Qwen3-VL 30B — good quality/accessibility tradeoff for vision MoE.

Quick start

ollama run qwen3-vl:30b

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.