Qwen 3.7 — Local AI Model by Alibaba Cloud

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

PREVIEW (June 2026, specs unverified). Alibaba's follow-up to Qwen 3.6 — a 35B-A3B MoE with native multimodal input, Apache 2.0, and ~256K context (extensible). Consumer-runnable at Q4. Numbers carried from the Qwen 3.6 lineage; verify against the Hugging Face model card.

Hardware Requirements

Qwen 3.7 35B-A3BMin 22 GB VRAM · Q4_K_M · 262,144 ctx ·

Recommended GPU

The cheapest GPU that runs Qwen 3.7 locally (min 22 GB VRAM) is the AMD Radeon RX 7900 XTX (24 GB).

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AMD Radeon RX 7900 XTX 24GB
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How to Run Locally

Install Ollama then run: ollama run

Minimum VRAM: 22 GB. For best results use Q4_K_M quantization.

Qwen 3.7 — Frequently Asked Questions

How much VRAM does Qwen 3.7 need?

Qwen 3.7 needs about 22 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Qwen 3.7 35B-A3B (22 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Qwen 3.7 on an RTX 4090 (24 GB)?

Yes — Qwen 3.7 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for Qwen 3.7?

Q4_K_M is the best balance of quality and VRAM for Qwen 3.7 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Qwen 3.7 with Ollama?

Install Ollama, then run: ollama run . This downloads Qwen 3.7 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.