Research: A free 300M Gemma model predicts Gemini embeddings at 0.83 cosine similarity
dejanseo · x · 2026-08-14
Research demonstrates that a single 768×768 matrix can map vectors from Google's free, local Gemma-300m model onto the output of the paid gemini-embedding-001 API. On 50,000 held-out Wikidata entities, the mapped vector achieves a 0.83 cosine similarity to the true Gemini vector. A pure rotation recovers 0.77, while adding stretch and shear raises it to 0.831, effectively recovering the entity vector structure without API costs.
More from Research
- Researcher slams papers whose stacked changes beat even weak baselines barely — retr0jirachi · 2026-10-16
- FrankenSim builds a physics-based virtual orchestra, piano and drum demos live — doodlestein · 2026-10-16
- FoveaVLA replaces wrist cameras with learned foveation, hitting 70.8% success — Haoyu_Xiong_ · 2026-10-16
- ApolloPFN: a zero-shot forecasting network that natively handles exogenous covariates — burkov · 2026-10-16
- ICLR reviewer says 4/5 papers in review pile read like AI slop — berkustun · 2026-10-16
- Tsinghua's DBS learns content-adaptive frequency band splits for audio source separation — thu-ml · 2026-10-16