What are the hardware requirements for Qwen 2.5 Math 7B Max V3 Accuracy?

Qwen 2.5 Math 7B Max V3 Accuracy requires approximately 15.2 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen 2.5 Math 7B Max V3 Accuracy and how large is it?

Qwen 2.5 Math 7B Max V3 Accuracy is developed by cg666, 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 Qwen 2.5 Math 7B Max V3 Accuracy?

Qwen 2.5 Math 7B Max V3 Accuracy is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen 2.5 Math 7B Max V3 Accuracy by cg666 — VRAM 15.2GB, 4K context

Name: Qwen 2.5 Math 7B Max V3 Accuracy
Author: cg666

Qwen 2.5 Math 7B Max V3 Accuracy is an open-source language model by cg666. Features: 7b LLM, VRAM: 15.2GB, Context: 4K, LLM Explorer Score: 0.17.

Arxiv:2402.03300 Base model:cg666/qwen-2.5-math... Base model:finetune:cg666/qwen... Conversational Dataset:digitallearninggmbh/ma... Endpoints compatible Generated from trainer Grpo Open-r1 Qwen2 Region:us Safetensors Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/cg666/Qwen-2.5-Math-7B-Max-v3-accuracy

Qwen 2.5 Math 7B Max V3 Accuracy Parameters and Internals

LLM Name	Qwen 2.5 Math 7B Max V3 Accuracy
Repository 🤗	https://huggingface.co/cg666/Qwen-2.5-Math-7B-Max-v3-accuracy
Model Name	Qwen-2.5-Math-7B-Max-v3-accuracy
Base Model(s)	chenggong1995/Qwen-2.5-Math-7B-Max-v3-accuracy chenggong1995/Qwen-2.5-Math-7B-Max-v3-accuracy
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-07-27
Maintainer	cg666
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
Context Length	4096
Model Max Length	4096
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen 2.5 Math 7B Max V3 Accuracy 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

Best Alternatives to Qwen 2.5 Math 7B Max V3 Accuracy

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
Rewnozom	986K / 30.5 GB	742	1
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

Note: green Score (e.g. "73.2") means that the model is better than cg666/Qwen-2.5-Math-7B-Max-v3-accuracy.