Vertex 0.6 15M Instruct
A tiny (~15M-param) chat model from the Vertex 0.6 family. Qwen3 architecture (hidden 256, 10 layers, GQA, 20000 vocab, ctx 2048), pretrained from scratch on 12B tokens of Ultra-FineWeb and Ultra-FineWeb-L3 English (natural + synthetic-rewrite mix), then taken through a custom post-training pipeline for chat.
What it does: coherent multi-turn chat with in-context memory (recalls your name/details from 1000+ tokens back, and says so honestly when you haven't told it).
What it doesn't do: facts, reasoning, math, code. At this size, knowledge is decorative — treat outputs as conversation, not information.
Usage
ChatML template (embedded). Sampling strongly recommended — greedy decoding loops badly at this size:
temperature 0.6, top_p 0.9, repeat_penalty 1.3
GGUF builds: Vertex-0.6-15M-Instruct-GGUF.
Trained end-to-end on a single RTX 4060 Laptop (8GB).
Training data
Fine-tuned from Vertex-0.6-15M-Base (pretrained on openbmb/Ultra-FineWeb + openbmb/Ultra-FineWeb-L3, 12B tokens). Instruction tuning was done with a custom post-training pipeline.