What are the hardware requirements for Qwenmplus?

Qwenmplus 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 Qwenmplus and how large is it?

Qwenmplus 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.

How does Qwenmplus perform on standard benchmarks?

Qwenmplus has the following published scores: LMSYS ELO 1315. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwenmplus by sumink — VRAM 6.2GB, 32K context

Name: Qwenmplus
Author: sumink

Qwenmplus is an open-source language model by sumink. Features: 1.5b LLM, VRAM: 6.2GB, Context: 32K, License: other, LLM Explorer Score: 0.31, ELO: 1315.

Qwen2 Region:us Safetensors Sharded Tensorflow

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

Qwenmplus Benchmarks

LMSys ELO 1315 vs 1272 (so35) 3.4%

^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)

Qwenmplus Parameters and Internals

LLM Name	Qwenmplus
Repository 🤗	https://huggingface.co/sumink/Qwenmplus
Model Size	1.5b
Required VRAM	6.2 GB
Updated	2026-08-06
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

Rank the Qwenmplus 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 Qwenmplus

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	11	0
ReaderLM V2	500K / 3.1 GB	35356	804
Reader Lm 1.5B	250K / 3.1 GB	385	608
DeepSeek R1 Distill Qwen 1.5B	128K / 3.5 GB	600051	1545
Ko R1 1.5B Preview	128K / 7.1 GB	8	9
Qwen2.5 1.5B	128K / 3.1 GB	863295	203
VibeThinker 1.5B	128K / 3.5 GB	3417	552
Merge Cord V1	128K / 3.1 GB	155	1
...FT Tulu3 Decontaminated Masked	128K / 3.1 GB	167	0
Qwen2 1.5B	128K / 3.1 GB	195380	102

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