What are the hardware requirements for YandexGPT 5 Lite 8B Instruct Q2?

YandexGPT 5 Lite 8B Instruct Q2 requires approximately 2.5 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 YandexGPT 5 Lite 8B Instruct Q2 and how large is it?

YandexGPT 5 Lite 8B Instruct Q2 is developed by mlx-community, a model with 8b 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 YandexGPT 5 Lite 8B Instruct Q2?

YandexGPT 5 Lite 8B Instruct Q2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

YandexGPT 5 Lite 8B Instruct Q2 by mlx-community — VRAM 2.5GB, 32K context

Name: YandexGPT 5 Lite 8B Instruct Q2
Author: mlx-community

YandexGPT 5 Lite 8B Instruct Q2 is an open-source language model by mlx-community. Features: 8b LLM, VRAM: 2.5GB, Context: 32K, Quantized, Instruction-Based, LLM Explorer Score: 0.21.

2-bit Base model:quantized:yandex/ya... Base model:yandex/yandexgpt-5-... Conversational Instruct Llama Mlx Q2 Quantized Region:us Ru Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/YandexGPT-5-Lite-8B-instruct-q2

YandexGPT 5 Lite 8B Instruct Q2 Parameters and Internals

LLM Name	YandexGPT 5 Lite 8B Instruct Q2
Repository 🤗	https://huggingface.co/mlx-community/YandexGPT-5-Lite-8B-instruct-q2
Base Model(s)	YandexGPT 5 Lite 8B Instruct yandex/YandexGPT-5-Lite-8B-instruct
Model Size	8b
Required VRAM	2.5 GB
Updated	2026-07-18
Maintainer	mlx-community
Model Type	llama
Instruction-Based	Yes
Model Files	2.5 GB
Supported Languages	ru
Quantization Type	q2
Model Architecture	LlamaForCausalLM
Context Length	32768
Model Max Length	32768
Tokenizer Class	LlamaTokenizer
Vocabulary Size	129024
Torch Data Type	float16

Rank the YandexGPT 5 Lite 8B Instruct Q2 capabilities

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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

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