What are the hardware requirements for MNLP M2 Mcqa Model?

MNLP M2 Mcqa Model requires approximately 1.2 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 MNLP M2 Mcqa Model and how large is it?

MNLP M2 Mcqa Model is developed by sophiargh, a model with 0.6b 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 MNLP M2 Mcqa Model?

MNLP M2 Mcqa Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MNLP M2 Mcqa Model by sophiargh — VRAM 1.2GB, 32K context

Name: MNLP M2 Mcqa Model
Author: sophiargh

MNLP M2 Mcqa Model is an open-source language model by sophiargh. Features: 0.6b LLM, VRAM: 1.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.18.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-0.6b-bas... Conversational Endpoints compatible Generated from trainer Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/sophiargh/MNLP_M2_mcqa_model

MNLP M2 Mcqa Model Parameters and Internals

LLM Name	MNLP M2 Mcqa Model
Repository 🤗	https://huggingface.co/sophiargh/MNLP_M2_mcqa_model
Base Model(s)	Qwen/Qwen3-0.6B-Base Qwen/Qwen3-0.6B-Base
Model Size	0.6b
Required VRAM	1.2 GB
Updated	2026-08-01
Maintainer	sophiargh
Model Type	qwen3
Model Files	1.2 GB 0.0 GB
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the MNLP M2 Mcqa Model 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 MNLP M2 Mcqa Model

Best Alternatives	Context / RAM	Downloads	Likes
S1 Mini	40K / 1.5 GB	1136	180
Qwen3 Reranker 0.6B	40K / 1.2 GB	2508313	377
Qwen3 0.6B JSON SFT	40K / 1.2 GB	428	1
RIFA Edge 0.6B	40K / 1.2 GB	581	0
Qwen3 0.6B FP8	40K / 1.1 GB	1581403	62
Meridian Ac Nano	40K / 1.2 GB	570	1
Qwen3 0.6B JSON SFT	40K / 1.2 GB	1676	0
Blake Haiku 1	40K / 1.2 GB	386	0
Tenorio 0.6B	40K / 1.2 GB	251	2
Quipu 0.6B	40K / 1.2 GB	351	4

Note: green Score (e.g. "73.2") means that the model is better than sophiargh/MNLP_M2_mcqa_model.