Model Releases
Will small model intelligence be limited by parameter count?
Qwen3.6-27b is fantastic! It makes me wonder if there's a hard ceiling to smaller sized models. Do you guys think the ceiling of intelligence for smaller models will be constrained by factors like par
Qwen3.6-27b is fantastic! It makes me wonder if there's a hard ceiling to smaller sized models. Do you guys think the ceiling of intelligence for smaller models will be constrained by factors like parameter count, or VRAM size? Or will we continue to see improvements for small models and see jumps of intelligence like Qwen3 coder 30b to Qwen3.6 27b for the foreseeable future? Does it depend on how clean the dataset you put into those parameters? What does /r/LocalLLama think about the future of small models that can run on less than 48GB of VRAM? submitted by /u/Sevealin_ [link] [comments]
Related
- I released Inflect v2: two ultra-tiny complete TTS models under 4M and 10M parameters
- MoE models around A2B
- Deepseek V4 flash - Hy3 or is Qwen3.6 27B still the most solid for agentic/coding?
- MindControl - llama.cpp fork to guide the reasoning process via injection during sampling
Source: r/LocalLLaMA | 2026-07-26