What are the hardware requirements for Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned?

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned requires approximately 0.3 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned?

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned by kshitijthakkar — VRAM 0.3GB, 1K context

Name: Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned
Author: kshitijthakkar

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned is an open-source language model by kshitijthakkar. Features: 133.4m LLM, VRAM: 0.3GB, Context: 1K, License: apache-2.0, MoE, Fine-Tuned, Instruction-Based, LLM Explorer Score: 0.19.

Agentic-ai Conversational Dataset:kshitijthakkar/loggeni... Edge-ai Endpoints compatible Finetuned From-scratch Instruct Instruction-following Low-resource Mixture-of-experts Moe Qwen3 Qwen3 moe Qwen3moe Region:us Safetensors Tool-use

Model Card on HF 🤗: https://huggingface.co/kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned Parameters and Internals

LLM Name	Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned
Repository 🤗	https://huggingface.co/kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned
Model Size	133.4m
Required VRAM	0.3 GB
Updated	2026-07-18
Maintainer	kshitijthakkar
Model Type	qwen3_moe
Instruction-Based	Yes
Model Files	0.3 GB
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned 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 Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned

Best Alternatives	Context / RAM	Downloads	Likes
... 0.12B A0.08B E5 Lr5e4 B4 3060	1K / 0.3 GB	14	1

Note: green Score (e.g. "73.2") means that the model is better than kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned.