What are the hardware requirements for First Mcqa Model?

First Mcqa Model requires approximately 2.4 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 First Mcqa Model and how large is it?

First Mcqa Model is developed by liam-mnlp, a model with 596m 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 First Mcqa Model?

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

First Mcqa Model by liam-mnlp — VRAM 2.4GB, 32K context

Name: First Mcqa Model
Author: liam-mnlp

First Mcqa Model is an open-source language model by liam-mnlp. Features: 596m LLM, VRAM: 2.4GB, Context: 32K, LLM Explorer Score: 0.18.

Base model:finetune:liam-mnlp/... Base model:liam-mnlp/mnlp m2 m... Conversational Endpoints compatible Generated from trainer Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/liam-mnlp/first-mcqa-model

First Mcqa Model Parameters and Internals

LLM Name	First Mcqa Model
Repository 🤗	https://huggingface.co/liam-mnlp/first-mcqa-model
Base Model(s)	MNLP M2 Mcqa Model liam-mnlp/MNLP_M2_mcqa_model
Model Size	596m
Required VRAM	2.4 GB
Updated	2026-07-25
Maintainer	liam-mnlp
Model Type	qwen3
Model Files	2.4 GB 0.0 GB
Model Architecture	Qwen3ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the First 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 First Mcqa Model

Best Alternatives	Context / RAM	Downloads	Likes
S1 Mini MLX Bf16	40K / 1.2 GB	218	1
Test6	40K / 1.2 GB	15	0
... Calling Qwen0.6B 27jul Merged	40K / 1.2 GB	670	0
...Qwen0.6B 27jul Merged Llamacpp	40K / 1.2 GB	5	0
Sam Reason A1	40K / 2.4 GB	20	1
Qwen3 0p6mimo S3 Bf161200	32K / 1.2 GB	117	0
Qwen3 Grpo2 96	32K / 1.2 GB	5	0
Qwen3 0p6 Bf16 600	32K / 1.2 GB	6	0
Rubi No Reason Phase 2	32K / 1.2 GB	11	0
Rubi No Reason Phase 1	32K / 1.2 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than liam-mnlp/first-mcqa-model.