Model reference · open weights

speech-large-114K

Embeddings PantagrueLLM Embeddings 1 build Its own licence terms 728 dl/mo

speech-large-114K is an open-weight embedding model from PantagrueLLM. speech-large-114K (FP32) weighs 627 MB; the smallest configuration that runs it is RTX 3060 12 GB.

  • speech-large-114K is a 313M parameter self-supervised encoder developed by PantagrueLLM for French speech feature extraction.
  • The model was pre-trained on diverse French audio data using a data2vec 2.0 teacher-student setup to learn contextualized representations.
  • It supports 16 kHz mono audio input and is distributed under an other licence.

Summary of the PantagrueLLM/speech-large-114K model card, 2026-10-01

What it is

Released byPantagrueLLM
Released2025-10-06
Parameters313M
VRAM627 MB for the weights

What it runs on

Memory and cards for speech-large-114K (FP32)

627 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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