What are the hardware requirements for Qmerft?

Qmerft requires approximately 3.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qmerft and how large is it?

Qmerft is developed by sumink, 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 Qmerft?

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

Qmerft by sumink — VRAM 3.5GB, 128K context

Name: Qmerft
Author: sumink

Qmerft is an open-source language model by sumink. Features: 1.5b LLM, VRAM: 3.5GB, Context: 128K, Merged, LLM Explorer Score: 0.17.

Merged Model Base model:qwen/qwen2.5-1.5b Base model:sumink/qwenftmodel Conversational Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/sumink/Qmerft

Qmerft Parameters and Internals

LLM Name	Qmerft
Repository 🤗	https://huggingface.co/sumink/Qmerft
Base Model(s)	Qwen/Qwen2.5-1.5B Qwenftmodel Qwen/Qwen2.5-1.5B sumink/Qwenftmodel
Merged Model	Yes
Model Size	1.5b
Required VRAM	3.5 GB
Updated	2026-07-26
Maintainer	sumink
Model Type	qwen2
Model Files	3.5 GB: 1-of-1
Model Architecture	Qwen2ForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qmerft 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 Qmerft

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	11	0
ReaderLM V2	500K / 3.1 GB	35356	804
Reader Lm 1.5B	250K / 3.1 GB	385	608
DeepSeek R1 Distill Qwen 1.5B	128K / 3.5 GB	600051	1545
Ko R1 1.5B Preview	128K / 7.1 GB	8	9
Qwen2.5 1.5B	128K / 3.1 GB	863295	203
VibeThinker 1.5B	128K / 3.5 GB	3417	552
Merge Cord V1	128K / 3.1 GB	155	1
...FT Tulu3 Decontaminated Masked	128K / 3.1 GB	167	0
Qwen2 1.5B	128K / 3.1 GB	195380	102

Note: green Score (e.g. "73.2") means that the model is better than sumink/Qmerft.