What are the hardware requirements for Lytta2.5 32B Instruct?

Lytta2.5 32B Instruct requires approximately 65.5 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 Lytta2.5 32B Instruct and how large is it?

Lytta2.5 32B Instruct is developed by maldv, a model with 32b 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 Lytta2.5 32B Instruct?

Lytta2.5 32B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Lytta2.5 32B Instruct by maldv — VRAM 65.5GB, 32K context

Name: Lytta2.5 32B Instruct
Author: maldv

Lytta2.5 32B Instruct is an open-source language model by maldv. Features: 32b LLM, VRAM: 65.5GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.23.

Base model:finetune:nextglab/o... Base model:nextglab/oransight ... Chat Conversational En Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/maldv/Lytta2.5-32B-Instruct

Lytta2.5 32B Instruct Parameters and Internals

LLM Name	Lytta2.5 32B Instruct
Repository 🤗	https://huggingface.co/maldv/Lytta2.5-32B-Instruct
Base Model(s)	maldv/Qwentile2.5-32B-Instruct prnshv/ORANSight_Qwen_32B_Instruct crestf411/Q2.5-32B-Slush allura-org/Qwen2.5-32b-RP-Ink Sao10K/32B-Qwen2.5-Kunou-v1 QwQ 32B Preview Abliterated ...s Horizon AI Japanese Base 32B maldv/Qwentile2.5-32B-Instruct prnshv/ORANSight_Qwen_32B_Instruct crestf411/Q2.5-32B-Slush allura-org/Qwen2.5-32b-RP-Ink Sao10K/32B-Qwen2.5-Kunou-v1 huihui-ai/QwQ-32B-Preview-abliterated Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B
Model Size	32b
Required VRAM	65.5 GB
Updated	2026-07-15
Maintainer	maldv
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.5 GB: 1-of-17 4.3 GB: 2-of-17 3.9 GB: 3-of-17 3.9 GB: 4-of-17 3.9 GB: 5-of-17 3.9 GB: 6-of-17 3.9 GB: 7-of-17 3.9 GB: 8-of-17 3.9 GB: 9-of-17 3.9 GB: 10-of-17 3.9 GB: 11-of-17 3.9 GB: 12-of-17 3.9 GB: 13-of-17 3.9 GB: 14-of-17 3.9 GB: 15-of-17 3.9 GB: 16-of-17 3.1 GB: 17-of-17
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.43.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Lytta2.5 32B Instruct capabilities

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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 Lytta2.5 32B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	28	17
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	22	4
Franqwenstein 35B	128K / 69.8 GB	5	8
ELYZA Thinking 1.0 Qwen 32B	128K / 65.8 GB	23	10
Archaeo 32B KTO	128K / 65.8 GB	19	4
Hamanasu Magnum QwQ 32B	128K / 65.8 GB	295	9
Qwen2.5 32B Gokgok Step3	128K / 65.7 GB	6	0
Openthaigpt R1 32B Instruct	128K / 65.8 GB	33	8
Qwen2.5 32B Dark Days Stage2	128K / 65.8 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than maldv/Lytta2.5-32B-Instruct.