What are the hardware requirements for TEN Turn Detection?

TEN Turn Detection requires approximately 15.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed TEN Turn Detection and how large is it?

TEN Turn Detection is developed by TEN-framework, a model with 7.6b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate TEN Turn Detection?

TEN Turn Detection is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

TEN Turn Detection by TEN-framework — VRAM 15.2GB, 32K context

Name: TEN Turn Detection
Author: TEN-framework

TEN Turn Detection is an open-source language model by TEN-framework. Features: 7.6b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.19.

Conversational Natural language understanding Region:us Safetensors Sharded Tensorflow Turn detection

Model Card on HF 🤗: https://huggingface.co/TEN-framework/TEN_Turn_Detection

TEN Turn Detection Parameters and Internals

LLM Name	TEN Turn Detection
Repository 🤗	https://huggingface.co/TEN-framework/TEN_Turn_Detection
Model Size	7.6b
Required VRAM	15.2 GB
Updated	2026-08-07
Maintainer	TEN-framework
Model Type	qwen2
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.50.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the TEN Turn Detection capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to TEN Turn Detection

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Quasar 3.7	986K / 15.2 GB	805	0
Quasar 3.3 Max	986K / 15.2 GB	132	0
MQ Coldbrew Base	128K / 15.2 GB	761	0
MawaredT1	128K / 15.2 GB	2318	1
Mergekit 01	128K / 16.2 GB	6	0
BBALAW1.6	128K / 15.2 GB	7	0
BBAI 525 Tsu GZ Xia0	128K / 15.2 GB	8	0
Nature Reason 1.2 Reallysmall	128K / 15.2 GB	27	1
Exp 3 Q R	128K / 15.2 GB	6	0
Math Custom Data	128K / 15.2 GB	11	0

Note: green Score (e.g. "73.2") means that the model is better than TEN-framework/TEN_Turn_Detection.