Small-Models
Qwen 3.5 Small Models: The 9B Beats Last-Gen 30B — Here's What Matters for Local AI
Alibaba's Qwen 3.5 drops 4 small models (0.8B to 9B) — all natively multimodal, 262K context, Apache 2.0. The 9B beats Qwen3-30B on reasoning and destroys GPT-5-Nano on vision. VRAM tables and what to run.
Ouro-2.6B-Thinking: ByteDance's Looped Model That Punches Like an 8B
Ouro-2.6B loops through the same transformer blocks 4 times to match 8B models at 2.6B parameters. Under 2GB at Q4. How the architecture works and why it matters.
PaddleOCR-VL: A 0.9B OCR Model That Runs on Any Potato
PaddleOCR-VL does document OCR — text, tables, formulas, charts — in 0.9B parameters. 109 languages. Now runs via llama.cpp and Ollama. Private, local, nearly free.
Phi Models Guide: Microsoft's Small but Mighty LLMs
Phi-4 14B scores 84.8% on MMLU — matching models 5x its size — and fits on a 12GB GPU at Q4. The full Phi lineup from 3.8B to 14B with VRAM needs, benchmarks, and honest weaknesses.
Best Models Under 3B: Small LLMs That Work
The best models under 3B parameters for laptops, old GPUs, Raspberry Pi, and phones. What works, what doesn't, and which tiny LLM to pick for your use case.