What are the hardware requirements for Qwensci?

Qwensci requires approximately 6.2 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 Qwensci and how large is it?

Qwensci 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 Qwensci?

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

Qwensci by sumink — VRAM 6.2GB, 32K context

Name: Qwensci
Author: sumink

Qwensci is an open-source language model by sumink. Features: 1.5b LLM, VRAM: 6.2GB, Context: 32K, License: other, LLM Explorer Score: 0.18.

Qwen2 Region:us Safetensors Sharded Tensorflow

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

Qwensci Benchmarks

LLME Score: 0.17743

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

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Qwensci Parameters and Internals

LLM Name	Qwensci
Repository 🤗	https://huggingface.co/sumink/Qwensci
Model Size	1.5b
Required VRAM	6.2 GB
Updated	2026-06-04
Maintainer	sumink
Model Type	qwen2
Model Files	5.0 GB: 1-of-2 1.2 GB: 2-of-2
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.47.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	[PAD]
Vocabulary Size	151666
Torch Data Type	float32
Errors	replace

Best Alternatives to Qwensci

Best Alternatives	Context / RAM	Downloads	Likes
ReaderLM V2	500K / 3.1 GB	371893	792
Reader Lm 1.5B	250K / 3.1 GB	376	607
DeepSeek R1 Distill Qwen 1.5B	128K / 3.5 GB	624689	1529
VibeThinker 1.5B	128K / 3.5 GB	3958	551
Ko R1 1.5B Preview	128K / 7.1 GB	8	9
Qwen2.5 1.5B	128K / 3.1 GB	1300274	191
Qwen2 1.5B	128K / 3.1 GB	195380	102
Polyalign Qwen2.5 1.5B En Sft	128K / 6.2 GB	40	0
...n Research Reasoning Qwen 1.5B	128K / 7.1 GB	5259	241
Gte Qwen2 1.5B Instruct	128K / 7.1 GB	822211	236

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

Rank the Qwensci Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Qwensci by sumink

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Qwensci Benchmarks

Qwensci Parameters and Internals

Best Alternatives to Qwensci

Rank the Qwensci Capabilities

What open-source LLMs or SLMs are you in search of? 54964 in total.