Model reference · open weights

surveybot3000

Embeddings magnolia-psychometrics Embeddings 1 build Licence not stated 500 dl/mo

surveybot3000 is an open-weight embedding model from magnolia-psychometrics. surveybot3000 (FP32) weighs 219 MB; the smallest configuration that runs it is RTX 3060 12 GB.

  • surveybot3000 is a sentence-transformers model developed by magnolia-psychometrics for the sentence-similarity task.
  • It maps sentences and paragraphs to a 768-dimensional dense vector space, supporting applications such as clustering and semantic search.
  • The model contains 109M parameters, uses the MPNet architecture, and has a maximum sequence length of 384 tokens.

Summary of the magnolia-psychometrics/surveybot3000 model card, 2026-10-01

What it is

Released bymagnolia-psychometrics
Released2024-04-19
Parameters109M
VRAM219 MB for the weights

What it runs on

Memory and cards for surveybot3000 (FP32)

219 MBweights, file size
1.1 GBruntime overhead
CardRunsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together, which is the basis of search and RAG.
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