What are the hardware requirements for Gte Qwen2 1.5B Instruct?

Gte Qwen2 1.5B Instruct requires approximately 7.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gte Qwen2 1.5B Instruct and how large is it?

Gte Qwen2 1.5B Instruct is developed by Alibaba-NLP, 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.

How does Gte Qwen2 1.5B Instruct perform on standard benchmarks?

Gte Qwen2 1.5B Instruct has the following published scores: MMLU 39.9. Compare against reference models on this page or on the LLM Explorer leaderboards.

Gte Qwen2 1.5B Instruct by Alibaba-NLP — VRAM 7.1GB, 128K context

Name: Gte Qwen2 1.5B Instruct
Author: Alibaba-NLP

Gte Qwen2 1.5B Instruct is an open-source language model by Alibaba-NLP. Features: 1.5b LLM, VRAM: 7.1GB, Context: 128K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.23, Arc: 50.6, HellaSwag: 29.6, MMLU: 39.9, GSM8K: 6.7.

Arxiv:2308.03281 Custom code Endpoints compatible Instruct Model-index Mteb Qwen2 Region:us Safetensors Sentence-similarity Sentence-transformers Sharded Tensorflow Text-embeddings-inference

Model Card on HF 🤗: https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct

Gte Qwen2 1.5B Instruct Parameters and Internals

Model Type

Sentence Similarity

Additional Notes

The model uses bidirectional attention mechanisms and is trained on a vast multilingual text corpus.

Input Output

Input Format:

text input with queries and documents

Accepted Modalities:

text

Output Format:

similarity scores

LLM Name	Gte Qwen2 1.5B Instruct
Repository 🤗	https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct
Model Size	1.5b
Required VRAM	7.1 GB
Updated	2026-09-20
Maintainer	Alibaba-NLP
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 2.1 GB: 2-of-2
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.41.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151646
Torch Data Type	float32
Errors	replace

Rank the Gte Qwen2 1.5B Instruct 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 Gte Qwen2 1.5B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	18	0
Merge Cord V1	128K / 3.1 GB	155	1
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
Deepthink 1.5B Open PRM	128K / 7.1 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than Alibaba-NLP/gte-Qwen2-1.5B-instruct.