What are the hardware requirements for Qwen Compassion Midtrain Seed2 CPT Best?

Qwen Compassion Midtrain Seed2 CPT Best requires approximately 16.4 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 Qwen Compassion Midtrain Seed2 CPT Best and how large is it?

Qwen Compassion Midtrain Seed2 CPT Best is developed by CompassioninMachineLearning, a model with 8b 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 Compassion Midtrain Seed2 CPT Best?

Qwen Compassion Midtrain Seed2 CPT Best is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen Compassion Midtrain Seed2 CPT Best by CompassioninMachineLearning — VRAM 16.4GB, 32K context

Name: Qwen Compassion Midtrain Seed2 CPT Best
Author: CompassioninMachineLearning

Qwen Compassion Midtrain Seed2 CPT Best is an open-source language model by CompassioninMachineLearning. Features: 8b LLM, VRAM: 16.4GB, Context: 32K, LLM Explorer Score: 0.3.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-8b-base Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/CompassioninMachineLearning/qwen-compassion-midtrain-seed2-CPT-best

Qwen Compassion Midtrain Seed2 CPT Best Parameters and Internals

LLM Name	Qwen Compassion Midtrain Seed2 CPT Best
Repository 🤗	https://huggingface.co/CompassioninMachineLearning/qwen-compassion-midtrain-seed2-CPT-best
Base Model(s)	Qwen3 8B Base Qwen/Qwen3-8B-Base
Model Size	8b
Required VRAM	16.4 GB
Updated	2026-10-14
Maintainer	CompassioninMachineLearning
Model Type	qwen3
Model Files	16.4 GB
Model Architecture	Qwen3ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Errors	replace

Rank the Qwen Compassion Midtrain Seed2 CPT Best 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

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PaCoRe 8B	320K / 1.2 GB	54	48
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...1 Qwen3 8B ArliAI RpR V4 Small	128K / 16.4 GB	182	1
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Note: green Score (e.g. "73.2") means that the model is better than CompassioninMachineLearning/qwen-compassion-midtrain-seed2-CPT-best.