What are the hardware requirements for Logics Parsing V3?

Logics Parsing V3 requires approximately 1.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Logics Parsing V3 and how large is it?

Logics Parsing V3 is developed by Logics-MLLM, a model with 853m 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 Logics Parsing V3?

Logics Parsing V3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Logics Parsing V3 by Logics-MLLM — VRAM 1.7GB

Name: Logics Parsing V3
Author: Logics-MLLM

Logics Parsing V3 is an open-source language model by Logics-MLLM. Features: 853m LLM, VRAM: 1.7GB, LLM Explorer Score: 0.32.

Arxiv:2603.09677 Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Logics-MLLM/Logics-Parsing-V3

Logics Parsing V3 Parameters and Internals

LLM Name	Logics Parsing V3
Repository 🤗	https://huggingface.co/Logics-MLLM/Logics-Parsing-V3
Model Size	853m
Required VRAM	1.7 GB
Updated	2026-09-25
Maintainer	Logics-MLLM
Model Type	qwen3_5
Model Files	1.7 GB
Model Architecture	Qwen3_5ForConditionalGeneration
Model Max Length	262144
Transformers Version	5.2.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Logics Parsing V3 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 Logics Parsing V3

Best Alternatives	Context / RAM	Downloads	Likes
STAGE1	0K / 1.7 GB	11	0