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

QVikhr 2.5 1.5B Instruct SMPO 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 SMPO and how large is it?

QVikhr 2.5 1.5B Instruct SMPO 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 SMPO?

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

Name: QVikhr 2.5 1.5B Instruct SMPO
Author: Vikhrmodels

QVikhr 2.5 1.5B Instruct SMPO 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:vikhrmodel... Base model:vikhrmodels/vikhr-q... Conversational En Endpoints compatible Instruct Qwen2 Region:us Ru Safetensors

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

QVikhr 2.5 1.5B Instruct SMPO Parameters and Internals

LLM Name	QVikhr 2.5 1.5B Instruct SMPO
Repository 🤗	https://huggingface.co/Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO
Model Name	Vikhrmodels/QVikhr-2.5-1.5B-Instruct-SMPO
Base Model(s)	Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct Vikhrmodels/Vikhr-Qwen-2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-07-12
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	4.47.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the QVikhr 2.5 1.5B Instruct SMPO 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

Quantized Models of the QVikhr 2.5 1.5B Instruct SMPO

Model	Likes	Downloads	VRAM
....5 1.5B Instruct SMPO MLX 4bit	3	25	0 GB
....5 1.5B Instruct SMPO MLX 8bit	2	8	1 GB

Best Alternatives to QVikhr 2.5 1.5B Instruct SMPO

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-SMPO.