What are the hardware requirements for Qwen2.5 1.5B Instruct CoT Reflection?

Qwen2.5 1.5B Instruct CoT Reflection 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 Qwen2.5 1.5B Instruct CoT Reflection and how large is it?

Qwen2.5 1.5B Instruct CoT Reflection is developed by mosama, 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 Qwen2.5 1.5B Instruct CoT Reflection?

Qwen2.5 1.5B Instruct CoT Reflection is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 1.5B Instruct CoT Reflection by mosama — VRAM 3.1GB, 32K context

Name: Qwen2.5 1.5B Instruct CoT Reflection
Author: mosama

Qwen2.5 1.5B Instruct CoT Reflection is an open-source language model by mosama. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.19.

Base model:finetune:unsloth/qw... Base model:unsloth/qwen2.5-1.5... Chat Conversational Cot Dataset:argilla/magpie-ultra-v... Dataset:mosama/cot-reflection En Endpoints compatible Instruct Qwen Qwen2 Reflection Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mosama/Qwen2.5-1.5B-Instruct-CoT-Reflection

Qwen2.5 1.5B Instruct CoT Reflection Parameters and Internals

LLM Name	Qwen2.5 1.5B Instruct CoT Reflection
Repository 🤗	https://huggingface.co/mosama/Qwen2.5-1.5B-Instruct-CoT-Reflection
Base Model(s)	unsloth/Qwen2.5-1.5B-Instruct unsloth/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-08-05
Maintainer	mosama
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 1.5B Instruct CoT Reflection 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 1.5B Instruct CoT Reflection

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	923076	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 mosama/Qwen2.5-1.5B-Instruct-CoT-Reflection.