Recent Open models from last 6 Months - Nov 2025 - Apr 2026
A viral chart tracks over 20 major open-source LLM releases from Nov 2025 to April 2026.
A viral analysis charting the open-source AI landscape from November 2025 to April 2026 reveals an unprecedented pace of development, with over 20 significant model releases in just six months. The community-created visualization focuses on the latest major versions from leading labs, including Moonshot AI's Kimi-K2.6, Zhipu AI's GLM-5.1 and GLM-4.7, and Alibaba's Qwen3.5-9B/4B. Notably, the chart creator had to exclude smaller models and some recent releases like Ling-2.5-1T to maintain clarity, underscoring the sheer volume of activity. This condensed timeline of innovation has led observers to dub it "possibly the best 6 months for Local LLMs," highlighting a golden age for developers who run models on their own hardware.
The chart serves as a stark indicator of the intense, global race in open AI, dominated by Chinese tech giants and research labs alongside Western contributors like Google's Gemma-4-E4B. This rapid-fire release cycle—featuring multiple version increments from single organizations—signals a shift from annual mega-releases to continuous, iterative improvement. For practitioners, this means more frequent access to state-of-the-art reasoning, coding, and multilingual capabilities without relying on closed APIs. The discussion now centers on which of these high-performing models are being overlooked, as the breakneck speed risks leaving gems undiscovered by the broader developer community.
- The chart tracks over 20 major open-source LLM releases from leading labs like Moonshot AI (Kimi), Zhipu AI (GLM), and Alibaba (Qwen) in a 6-month window.
- Development pace is so rapid the creator had to exclude smaller models and some releases (e.g., Ling-2.5-1T) to avoid clutter.
- The period from Nov 2025-Apr 2026 is being called "possibly the best 6 months for Local LLMs," indicating a surge in accessible, high-quality models.
Why It Matters
For developers, this explosion of open models means more power, choice, and control for building local AI applications without vendor lock-in.