What are the hardware requirements for FluentlyQwen2.5 32B?

FluentlyQwen2.5 32B 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 FluentlyQwen2.5 32B and how large is it?

FluentlyQwen2.5 32B is developed by fluently-lm, 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 FluentlyQwen2.5 32B?

FluentlyQwen2.5 32B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FluentlyQwen2.5 32B by fluently-lm — VRAM 65.8GB, 32K context

Name: FluentlyQwen2.5 32B
Author: fluently-lm

FluentlyQwen2.5 32B is an open-source language model by fluently-lm. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, License: mit, LLM Explorer Score: 0.17.

Argilla 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/FluentlyQwen2.5-32B

FluentlyQwen2.5 32B Parameters and Internals

LLM Name	FluentlyQwen2.5 32B
Repository 🤗	https://huggingface.co/fluently/FluentlyQwen2.5-32B
Model Size	32b
Required VRAM	65.8 GB
Updated	2026-07-26
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 FluentlyQwen2.5 32B 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 FluentlyQwen2.5 32B

Best Alternatives	Context / RAM	Downloads	Likes
Openbuddy Qwq 32B V24.2 200K	195K / 65.8 GB	9	3
Openbuddy Qwq 32B V24.1 200K	195K / 65.8 GB	10	3
Openbuddy Qwq 32B V25.2q 200K	195K / 65.8 GB	1	4
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
DeepSeek R1 Distill Qwen 32B	128K / 65.7 GB	841633	1584
Qwen2.5 32B	128K / 65.5 GB	49206	180
RomboUltima 32B	128K / 20.7 GB	12	6
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	42	17
Ultiima 32B	128K / 65.8 GB	11	7
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	13	4

Note: green Score (e.g. "73.2") means that the model is better than fluently/FluentlyQwen2.5-32B.