What are the hardware requirements for QVikhr 2.5 1.5B Instruct R?

QVikhr 2.5 1.5B Instruct R requires approximately 3.1 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 QVikhr 2.5 1.5B Instruct R and how large is it?

QVikhr 2.5 1.5B Instruct R is developed by Vikhrmodels, a model with 1.5b 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 QVikhr 2.5 1.5B Instruct R?

QVikhr 2.5 1.5B Instruct R is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

QVikhr 2.5 1.5B Instruct R by Vikhrmodels — VRAM 3.1GB, 32K context

Name: QVikhr 2.5 1.5B Instruct R
Author: Vikhrmodels

QVikhr 2.5 1.5B Instruct R is an open-source language model by Vikhrmodels. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.17.

Arxiv:2405.13929 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b Conversational Dataset:openai/gsm8k Dataset:vikhrmodels/russian ma... En Endpoints compatible Instruct Qwen2 Region:us Ru Safetensors

Model Card on HF 🤗: https://huggingface.co/Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r

QVikhr 2.5 1.5B Instruct R Parameters and Internals

LLM Name	QVikhr 2.5 1.5B Instruct R
Repository 🤗	https://huggingface.co/Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r
Model Name	Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r
Base Model(s)	Qwen/Qwen2.5-1.5B Qwen/Qwen2.5-1.5B
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-07-18
Maintainer	Vikhrmodels
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	ru en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the QVikhr 2.5 1.5B Instruct R 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 QVikhr 2.5 1.5B Instruct R

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	11	0
Merge Cord V1	128K / 3.1 GB	155	1
Gte Qwen2 1.5B Instruct	128K / 7.1 GB	899648	237
AceInstruct 1.5B	128K / 3.5 GB	139	22
... Abliterated TIES Qwen2.5 1.5B	128K / 3.5 GB	15	0
Saba1 1.8B	128K / 3.6 GB	6	1
Miniclaus Qw1.5B UNAMGS	128K / 3.5 GB	12	8
Bellatrix 1.5B XElite	128K / 3.5 GB	19	3
GCIRS Reasoning 1.5B R1	128K / 3.5 GB	9	1
...illed Scout 1.5B Instruct Gen1	128K / 3.5 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r.