What are the hardware requirements for FluentlyLM Prinum?

FluentlyLM Prinum requires approximately 65.8 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 FluentlyLM Prinum and how large is it?

FluentlyLM Prinum is developed by fluently-lm, a model with 32.8b 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 FluentlyLM Prinum?

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

FluentlyLM Prinum by fluently-lm — VRAM 65.8GB, 32K context

Name: FluentlyLM Prinum
Rating: 2.33 (3 reviews)
Author: fluently-lm

FluentlyLM Prinum is an open-source language model by fluently-lm. Features: 32.8b LLM, VRAM: 65.8GB, Context: 32K, License: mit, LLM Explorer Score: 0.32.

Argilla Autotrain compatible Axolotl Code Conversational Dataset:fluently-sets/math-500... Dataset:fluently-sets/reasonin... Dataset:fluently-sets/ultraset Dataset:fluently-sets/ultrathi... En Endpoints compatible Es Fa Fluently Fluently-lm Fr Instruct Ja Math Model-index Prinum Qwen2 Reasoning Region:us Roleplay Ru Safetensors Sharded Tensorflow Trained Unsloth Zh

Model Card on HF 🤗: https://huggingface.co/fluently-lm/FluentlyLM-Prinum

FluentlyLM Prinum Parameters and Internals

LLM Name	FluentlyLM Prinum
Repository 🤗	https://huggingface.co/fluently-lm/FluentlyLM-Prinum
Model Size	32.8b
Required VRAM	65.8 GB
Updated	2025-09-07
Maintainer	fluently-lm
Model Type	qwen2
Model Files	5.0 GB: 1-of-14 5.0 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 1.9 GB: 14-of-14
Supported Languages	en fr es ru zh ja fa code
Model Architecture	Qwen2ForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the FluentlyLM Prinum 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 FluentlyLM Prinum

Best Alternatives	Context / RAM	Downloads	Likes
AM Thinking V1	128K / 65.7 GB	79	205
Magnum Hamanasu QwQ V2 R1	128K / 65.8 GB	12	0
Magnum Hamanasu QwQ V2 R1	128K / 65.8 GB	10	0
DRIVE RL	64K / 65.6 GB	42	12
QwQ Med 3	40K / 131.5 GB	23	2
INTELLECT 2	40K / 131.5 GB	75	204
PathFinderAi3.0	32K / 65.8 GB	4	1
Vlsi MoE Ffn Merged	32K / 65.5 GB	9	0
...py Roleplay 1739875661 0711603	32K / 65.8 GB	54	0
...ppy Roleplay 1739875662 172876	32K / 65.8 GB	5	0