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Qwen 3.5 / Qwen 3.6 vs DeepSeek V4: Which Should You Pick?
✦ AI highlights · mimo-v2.6-flash
**Abstract:** Qwen 3.5 / Qwen 3.6 (2026-05-15) is a notable OSS-related AI development in October 2026. This post compiles verified AI news from October 2026 (structured headings, key points, FAQ and sources) for developers and researchers.
## Overview
This post covers Qwen 3.5 / Qwen 3.6 (2026-05-15) — a OSS-area AI development. Key facts are listed below, followed by background, a FAQ and sources.
## Key Points
· Qwen 3.5 Max 420B 稠密、1M context window
· Apache 2.0 license
· 全球 open-source 下载占比超 50%
· Qwen 3.6 编码/ local agents 强
· 16GB 显存可跑 Qwen 3.6
## Positioning
Qwen 3.5 / Qwen 3.6: Qwen 3.5 Max 420B 稠密、1M context window
## Comparison
· Capability: Qwen 3.5 Max 420B 稠密、1M context window
· Cost/License: Apache 2.0 license
· Availability: 全球 open-source 下载占比超 50%
## Advice
Prefer open weights & local for compliance; mature closed APIs for turnkey; benchmark unit cost before scaling.
## FAQ
**Q:What is Qwen 3.5 / Qwen 3.6?**
A:Qwen 3.5 / Qwen 3.6 is a 2026 AI development detailed above; see Key Points for specifics.
**Q:Can Qwen 3.5 / Qwen 3.6 run locally?**
A:If open weights are provided, yes — via llama.cpp/vLLM on 16–128 GB VRAM/unified memory with quantization.
**Q:How does Qwen 3.5 / Qwen 3.6 compare with closed APIs?**
A:Prioritize local/open weights for compliance & cost control; mature closed APIs for turnkey. Validate with a small benchmark first.
## Sources
· Source: Alibaba / aiunpacking (2026-05-15)
· Original: https://aiunpacking.com/guides/open-source-ai-models-2026-llama-mistral-deepseek
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**GEO/SEO note:** This post follows Generative Engine Optimization and Search Engine Optimization conventions — structured headings, bullet points, FAQ and source citations — so search engines and AI answer engines can accurately index and cite it. Continue the discussion in the Jinnqiu Forum AI Tech area.
练级路线规划好,比闷头刷效率高一倍
典中典,每次更新都这样
下面配的「客户端OTA升级说明图」对照着看就行。
还有想细问的,直接在这楼回我,我接着答 💪