What are the hardware requirements for Qwen2.5 7B Reasonmed Finetune Extreme?

Qwen2.5 7B Reasonmed Finetune Extreme 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 Qwen2.5 7B Reasonmed Finetune Extreme and how large is it?

Qwen2.5 7B Reasonmed Finetune Extreme is developed by Makrrr, a model with 7b 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 Qwen2.5 7B Reasonmed Finetune Extreme?

Qwen2.5 7B Reasonmed Finetune Extreme is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 7B Reasonmed Finetune Extreme by Makrrr — VRAM 15.2GB, 32K context

Name: Qwen2.5 7B Reasonmed Finetune Extreme
Author: Makrrr

Qwen2.5 7B Reasonmed Finetune Extreme is an open-source language model by Makrrr. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: other, Fine-Tuned, LLM Explorer Score: 0.19.

Base model:finetune:makrrr/qwe... Base model:makrrr/qwen2.5-7b-r... Conversational Endpoints compatible Finetuned Full Generated from trainer Llama-factory Qwen2 Region:us Safetensors Sharded Tensorboard Tensorflow

Model Card on HF 🤗: https://huggingface.co/Makrrr/qwen2.5-7B-reasonmed-finetune-extreme

Qwen2.5 7B Reasonmed Finetune Extreme Parameters and Internals

LLM Name	Qwen2.5 7B Reasonmed Finetune Extreme
Repository 🤗	https://huggingface.co/Makrrr/qwen2.5-7B-reasonmed-finetune-extreme
Base Model(s)	Makrrr/qwen2.5-7B-reasonmed-finetune-extreme Makrrr/qwen2.5-7B-reasonmed-finetune-extreme
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-04-26
Maintainer	Makrrr
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 0.0 GB
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.52.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 7B Reasonmed Finetune Extreme 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 Qwen2.5 7B Reasonmed Finetune Extreme

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Preview	986K / 15.2 GB	10	0
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B V1.2	986K / 15.2 GB	4	1
Hush Qwen2.5 7B V1.1	986K / 15.2 GB	5	1
Hush Qwen2.5 7B V1.4	986K / 15.2 GB	8	1
Hush Qwen2.5 7B Preview	986K / 15.2 GB	5	0
Hush Qwen2.5 7B V1.3	986K / 15.2 GB	10	2
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen 2.5 7B Exp Sce	986K / 15.2 GB	10	2
Qwen2.5 7B MixStock V0.1	986K / 15.2 GB	6	3

Note: green Score (e.g. "73.2") means that the model is better than Makrrr/qwen2.5-7B-reasonmed-finetune-extreme.