🧠
Lite Whisper Large V3 Turbo model by Efficient Speech
⭐ 35.4
🧠
Model

Lite Whisper Large V3 Turbo

by Efficient Speech efficient-speech/lite-whisper-large-v3-turbo
Free2AITools Nexus Index
35.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 46
P: Popularity 30
R: Recency 35
Q: Quality 65
Tech Context
0.61B Params
4.096K Ctx
Vital Performance
1.6K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 35.4 FNI Score
Tiny 0.61B Params
4k Context
1.6K Downloads
8G GPU ~2GB Est. VRAM
Dense LITEWHISPERFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID efficient-speech/lite-whisper-large-v3-turbo
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{efficient_speech_lite_whisper_large_v3_turbo,
  author = {Efficient Speech},
  title = {Lite Whisper Large V3 Turbo Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/efficient-speech/lite-whisper-large-v3-turbo}},
  note = {Accessed via Free2AITools.}
}
APA Style
Efficient Speech. (2025). Lite Whisper Large V3 Turbo [Model]. Free2AITools. https://huggingface.co/efficient-speech/lite-whisper-large-v3-turbo

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run lite-whisper-large-v3-turbo
πŸ€— HF Download
huggingface-cli download efficient-speech/lite-whisper-large-v3-turbo
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 46
Popularity (P) 30
Recency (R) 35
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Lite Whisper Large V3 Turbo: Authority (A:46), Popularity (P:30), Recency (R:35), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Deployment reference

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Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.

Social Proof

HuggingFace Hub
1.6KDownloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--efficient-speech--lite-whisper-large-v3-turbo
slug
efficient-speech--lite-whisper-large-v3-turbo
source
huggingface
author
Efficient Speech
license
Apache-2.0
tags
transformers, safetensors, lite-whisper, feature-extraction, audio, automatic-speech-recognition, whisper, hf-asr-leaderboard, custom_code, arxiv:2502.20583, base_model:openai/whisper-large-v3-turbo, base_model:finetune:openai/whisper-large-v3-turbo, license:apache-2.0, region:us, image-feature-extraction

βš™οΈ Technical Specs

architecture
LiteWhisperForConditionalGeneration
params billions
0.61
context length
4,096
pipeline tag
automatic-speech-recognition
vram gb
1.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
1,593
stars
0
forks
0

Data indexed from public sources. Updated daily.