Autor: Jakub Rusinowski · Ostatnia aktualizacja: 21 lipca 2026
Alibaba's most ambitious open-weight model release. Qwen 3.5 (397B) is a natively multimodal model supporting text, vision, and video understanding in a single architecture. Ranks among the top 3 open-weight models globally and competes directly with GPT-4o and Gemini 2.0 Pro on multimodal benchmarks.
| Qwen 3.5 14B | Min 10 GB VRAM · Q4_K_M · 128,000 ctx · ollama run qwen3.5:14b |
| Qwen 3.5 72B | Min 40 GB VRAM · Q4_K_M · 128,000 ctx · ollama run qwen3.5:72b |
| Qwen 3.5 397B | Min 200 GB VRAM · Q4_K_M · 128,000 ctx · ollama run qwen3.5:397b |
The cheapest GPU that runs Qwen 3.5 (Legacy Listing — Unverified) locally (min 10 GB VRAM) is the Intel Arc B570 (10 GB).
Install Ollama then run: ollama run qwen3.5:14b
Minimum VRAM: 10 GB. For best results use Q4_K_M quantization.
Qwen 3.5 (Legacy Listing — Unverified) needs about 10 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Qwen 3.5 14B (10 GB, Q4_K_M); Qwen 3.5 72B (40 GB, Q4_K_M); Qwen 3.5 397B (200 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Qwen 3.5 (Legacy Listing — Unverified) 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.
Q4_K_M is the best balance of quality and VRAM for Qwen 3.5 (Legacy Listing — Unverified) 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.
Install Ollama, then run: ollama run qwen3.5:14b. This downloads Qwen 3.5 (Legacy Listing — Unverified) and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.