Model reference · open weights
faster-whisper-large-hindi is an open-weight audio or speech model from collabora. faster-whisper-large-v2-hindi (BF16) weighs 3.1 GB; the smallest configuration that runs it is RTX 3060 12 GB.
Summary of the collabora/faster-whisper-large-v2-hindi model card, 2026-10-01
What it is
| Released by | collabora |
|---|---|
| Released | 2025-05-16 |
| VRAM | 3.1 GB for the weights |
What it runs on
| Card | One stream | Memory |
|---|---|---|
| RTX 3060 12 GB | fits | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
This repository contains the conversion of collabora/whisper-large-v2-hindi to the CTranslate2 model format.
This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.
from faster_whisper import WhisperModel
model = WhisperModel("collabora/faster-whisper-large-v2-hindi")
segments, info = model.transcribe("audio.mp3")
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
How it works